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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">farmaec</journal-id><journal-title-group><journal-title xml:lang="en">FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology</journal-title><trans-title-group xml:lang="ru"><trans-title>ФАРМАКОЭКОНОМИКА. Современная фармакоэкономика и фармакоэпидемиология</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2070-4909</issn><issn pub-type="epub">2070-4933</issn><publisher><publisher-name>IRBIS LLC</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17749/2070-4909/farmakoekonomika.2022.135</article-id><article-id custom-type="elpub" pub-id-type="custom">farmaec-732</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ORIGINAL ARTICLES</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОРИГИНАЛЬНЫЕ ПУБЛИКАЦИИ</subject></subj-group></article-categories><title-group><article-title>Dietary factors influencing the COVID-19 epidemic process</article-title><trans-title-group xml:lang="ru"><trans-title>Диетические факторы, влияющие на эпидемический процесс COVID-19</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Пономаренко</surname><given-names>С. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Ponomarenko</surname><given-names>S. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Пономаренко София Васильевна – к.б.н., менеджер проектов компании</p><p>Сименсштрассе, д. 42, Бёнен 59199</p></bio><bio xml:lang="en"><p>Sophia V. Ponomarenko – Dr. Rer. Nat., Projectmanager</p><p>42 Siemensstraße, Bönen 59199</p></bio><email xlink:type="simple">sp@sophigen.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">SophiGen inGr<country>Германия</country></aff><aff xml:lang="en">SophiGen inGr<country>Germany</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>18</day><month>01</month><year>2023</year></pub-date><volume>15</volume><issue>4</issue><fpage>463</fpage><lpage>471</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ponomarenko S.V., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Пономаренко С.В.</copyright-holder><copyright-holder xml:lang="en">Ponomarenko S.V.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.pharmacoeconomics.ru/jour/article/view/732">https://www.pharmacoeconomics.ru/jour/article/view/732</self-uri><abstract><sec><title>Objective</title><p>Objective: to analyze the role of diet in the epidemiological parameters of the SARS-CoV-2 Coronavirus and identify factors that correlate withthe reduction in the severity of the consequences of COVID-19 disease, namely the rate of prevalence (RPr) and infection fatality rate (IFR) in different regions.</p></sec><sec><title>Material and methods</title><p>Material and methods. The information and data required for this study were found in scientific publications and the media available on the Internet, as well as obtained from statistical databases using specific keywords, both for a single tag and in various combinations of them. Statistical samples were managed from sources and facts available on the Internet. Pearson correlation coefficient (r) was used to understand a statistical relationship between two variables.</p></sec><sec><title>Results</title><p>Results. The relationship between nutritional factors and the impact of the 15-month COVID-19 pandemic in different regions was investigated using various available statistics for five continents and 47 countries. A clear relationship was found between the outcomes of the SARSCoV-2 epidemic (RPr and IFR) and the amount of consumed essential nutrients, with correlations in the negative range r=–0.98 and r=–0.66 for plant proteins and with correlation coefficients r=0.92 for animal proteins. Also, excessive sugar consumption increased the severity of COVID-19 with correlation coefficients in the range of r=0.99–0.72 in the representative samples.</p></sec><sec><title>Conclusion</title><p>Conclusion. Statistical analysis presented that the number of diagnosed patients with SARS-CoV-2 (RPr) and deaths from COVID-19 (IFR) was significantly lower in regions where more plant foods were consumed than animal products. A detailed study of the relationship between the Coronavirus and the host as well as the metabolism of protein and sugar may reveal the diet factors responsible for resistance to the pathogen. Edible plants can contain components responsible for suppressing the replication cycle of the SARS-CoV-2 virus. Biochemical investigation of these components would help in the development of etiological oral administrated anti-COVID-9 medicine.</p></sec></abstract><trans-abstract xml:lang="ru"><sec><title>Цель</title><p>Цель: проанализировать роль рациона питания в эпидемиологических параметрах коронавируса SARS-CoV-2 и выявить факторы, коррелирующие со снижением тяжести последствий заболевания COVID-19, а именно частотой заболеваемости (англ. rate of prevalence, RPr) и смертности (англ. infection fatality rate, IFR) в разных регионах.</p></sec><sec><title>Материал и методы</title><p>Материал и методы. Информация и данные, необходимые для этой работы, были найдены в научных публикациях и средствах массовой информации, доступных в Интернете, а также получены из баз статистических данных с использованием определенных ключевых слов для одного тега или в различных их комбинациях. Статистические выборки были сформированы из источников и фактов, доступных в Интернете. Корреляция для двух переменных определялась как коэффициент Пирсона.</p></sec><sec><title>Результаты</title><p>Результаты. Взаимосвязь между факторами питания и влиянием 15-месячной пандемии COVID-19 в разных регионах была исследована с использованием различных доступных статистических данных по пяти континентам и 47 странам. Обнаружена четкая связь между исходами эпидемии SARS-CoV-2 (RPr и IFR) и количеством потребленных основных нутриентов с корреляциями в отрицательном диапазоне r=–0,98 и r=–0,66 для растительных белков и коэффициентом корреляции r=0,92 для белков животного происхождения. Также чрезмерное потребление сахара увеличивало тяжесть течения COVID-19 с коэффициентами корреляции в диапазоне r=0,99–0,72 в репрезентативных выборках.</p></sec><sec><title>Заключение</title><p>Заключение. Статистический анализ показал, что количество диагностированных пациентов с SARS-CoV-2 (RPr) и смертей от COVID-19 (IFR) было значительно ниже в регионах, где потреблялось больше растительной пищи, чем продуктов животного происхождения. Детальное изучение взаимосвязи между коронавирусом и хозяином, а также метаболизма белков и сахаров поможет выявить факторы питания, ответственные за устойчивость к патогену. Съедобные растения могут содержать компоненты, ответственные за подавление цикла репликации вируса SARS-CoV-2. Биохимические исследования этих компонентов помогут в разработке этиологических пероральных препаратов против COVID-19.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>Коронавирус SARS-CoV-2</kwd><kwd>пандемия COVID-19</kwd><kwd>эпидемия</kwd><kwd>патогенез</kwd><kwd>диета</kwd><kwd>факторы риска</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Сoronavirus SARS-CoV-2</kwd><kwd>COVID-19 pandemic</kwd><kwd>epidemic</kwd><kwd>pathogenesis</kwd><kwd>diet</kwd><kwd>risk factors.</kwd></kwd-group></article-meta></front><body><sec><title>INTRODUCTION / ВВЕДЕНИЕ</title><p>The current COVID-19 pandemic was announced by World Health Organization (WHO) on March 11, 2020 [<xref ref-type="bibr" rid="cit1">1</xref>]. The disease was caused by the highly transmitted from person to person SARS-CoV-2 coronavirus. COVID-19 (Corona Virus Infectious Disease) was detected in China at the end of 2019, and a newly discovered coronavirus was identified moreover, the genome of SARS-CoV-2 was rapidly sequenced [2–4]. This is a very dangerous infectious disease that affects a huge number of people on all continents and countries [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit6">6</xref>].</p><p>Epidemiologists and virologists have suggested that global infection with the highly pathogenic SARS-CoV-2 virus will continue for more than three years. The COVID-19 pandemic is a global health, medical, social, and economic challenge now and as well as in the future. Many diverse factors increasing the onset and course of COVID-19 disease have been evaluated and analyzed [<xref ref-type="bibr" rid="cit5">5</xref>][7–17].</p><p>This review analyzes the influence of dietary factors on the development of the SARS-CoV-2 epidemic process on five continents and in some of their regions to assess the effectiveness of factors that can reduce the consequences of severe infectious disease.</p></sec><sec><title>MATERIAL AND METHODS / МАТЕРИАЛ И МЕТОДЫ</title><p>Expected information was methodically investigated on the Internet using selected keywords. The keywords were managed as a single tag or in tags compositions. The statistical population groups were made from data from 47 countries. Most of the statistics were acquired from the following special and reliable databanks: World Health Organization1, Worldometer2, Food and Agriculture Organization3, Our World in Data4, The World Bank Open Data5, International Monetary Fund6.</p><p>The rate of prevalence (RPr) or infection fatality rate (IFR) of the virus was calculated as a ratio between the quantities of all cases and the total population. Case fatality rate (CFR) was the ratio between total COVID-19 deaths and the registered infection cases in %. The relationship between statistical data was calculated as a Pearson correlation coefficient (r).</p></sec><sec><title>RESULTS AND DISCUSSION / РЕЗУЛЬТАТЫ И ОБСУЖДЕНИЕ</title></sec><sec><title>Basic views about the etiology and pathogenesis of SARS-COV-2 / Основные представления об этиологии и патогенезе вируса SARS-COV-2</title><p>Discovered at the end of 2019, the new virus was announced by the International Committee on Taxonomy of Viruses as SARS-CoV-2. The large and combined RNA virus belongs to the genus Beta-coronavirus, the Coronaviridae family. Coronaviruses cause respiratory tract infections in birds and mammals. Betacoronaviruses are highly transmissible, enveloped, heavyweight, and complex RNA viruses that cause several acute respiratory infections in humans [2–4][<xref ref-type="bibr" rid="cit18">18</xref>]. The SARS-CoV-2 Beta-coronavirus is extremely contagious to humans, and pathogen virions spread among people through aerosol-generated particles and primarily enter type 2 pneumocytes attaching to the host angiotensin-converting enzyme (ACE2) [<xref ref-type="bibr" rid="cit2">2</xref>][<xref ref-type="bibr" rid="cit3">3</xref>][<xref ref-type="bibr" rid="cit19">19</xref>][<xref ref-type="bibr" rid="cit20">20</xref>].</p><p>Conventionally, the life cycle of pathogenic viruses transmitted by airborne droplets is determined by the main stages: infection, replication, release, and transmission of virions. The stage of infection includes the following phases: the presence of a sensitive object in the environment; invasion of the respiratory tract; transport to sensitive tissues and endocytosis into host cells. The replication stage consists of the following phases: synthesis of viral polypeptides and RNA; the formation of a protovirus; assembly of virion components. The third stage is: the exit of daughter virions from the cell, departure from the host, and spread. The genome of Сoronaviruses encodes the structure of several proteases that are important for the successful invasion and productive pathogen replication [2–4].</p><p>COVID-19 is currently known as a very dangerous infectious disease that causes fatal pathogenic symptoms. Five main variants of the severity of COVID-19 disease have been identified: asymptomatic, subclinical, acute with convalescence, chronic, and lethal [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit7">7</xref>][<xref ref-type="bibr" rid="cit8">8</xref>]. The predominantly clinical manifestation of COVID-19 is pneumonia, which can lead to SARS and critical lung damage in a very short time. Moreover, the virus is toxic and destructive to other human organs. The SARS-CoV-2 virus can destroy tissue and cause multiple organ failure during infection [<xref ref-type="bibr" rid="cit7">7</xref>][<xref ref-type="bibr" rid="cit8">8</xref>][<xref ref-type="bibr" rid="cit21">21</xref>][<xref ref-type="bibr" rid="cit22">22</xref>], as well as cause a dangerous post-COVID syndrome called Long-COVID [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit7">7</xref>][<xref ref-type="bibr" rid="cit23">23</xref>][<xref ref-type="bibr" rid="cit24">24</xref>]. In the current conditions of a pandemic, it would be very useful to find natural factors that prevent the development of a serious illness.</p></sec><sec><title>Consequences of the pandemic: fifteen months later / Последствия пандемии: пятнадцать месяцев спустя</title><p>On Thursday, June 10, 2021, 15 months have passed since the WHO announced the COVID-19 pandemic [<xref ref-type="bibr" rid="cit1">1</xref>], but no clear scientific prediction of the end date has yet been made. By this time, cases of infection have been confirmed in all countries and several thousand circulating variants of the SARS-CoV-2 virus have been identified [5–7]. New mutants with higher transmission rates are emerging in different regions, indicating that, there are no signs of weakening of the global pandemic. Most likely, the number of cases of infection will continue to increase in the form of growing waves.</p><p>This review discusses the COVID-19 pandemic data collected over the study period, March 11, 2020, to June 10, 2021. During the 15 months of the study-period, about 175.6 thousand cases of viral infection were confirmed globally, which is 2.25% of the world’s population [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit6">6</xref>]. The largest number of infected patients on this date was observed in Europe and Asia, together lived on these continents 57% of global infected with the virus SARS-CoV-2 [<xref ref-type="bibr" rid="cit6">6</xref>].</p><p>In North America (NA), the majority of those infected were in the United States of America (USA), South America in Brazil, Europe in France, Asia in India, and in Africa in South Africa [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit6">6</xref>]. In these five countries, almost 50% of the globally detected cases of the SARS-CoV-2 virus with the spread of special variants [5–7] were reported. However, the relative number of deaths in these countries from different continents varies considerably [<xref ref-type="bibr" rid="cit6">6</xref>].</p><p>On this date, about 4 million deaths were registered in the world, which was 2.16% of all infected patients. Until June 10, 2021, data on mortality from COVID-19 disease in the world grew in the form of four growing waves [<xref ref-type="bibr" rid="cit6">6</xref>]. As the number of people infected increases, the number of deaths will rise on all continents. Reducing the number of incidences and deaths from COVID-19 is an urgent task in the fight against coronavirus. To do this, it is important to analyze the epidemiological data and determine the factors that can reduce the pathogenesis of the SARS-CoV-2 virus.</p><p>Infection or mortality rates vary greatly from region to region and from country to country. These data may differ by a factor of a hundred or a thousand, which is why some publications question the fact that statistical information on epidemiological processes from different countries was reliable [<xref ref-type="bibr" rid="cit25">25</xref>]. Despite the opinion that the analysis of a large database has its drawbacks, which are especially evident with a heterogeneous sample [<xref ref-type="bibr" rid="cit26">26</xref>], for greater reliability, the influence of socio-economic factors on the course and outcomes of the SARS-CoV-2 coronavirus was analyzed using a large number of representative statistics and a long study period [27–29].</p></sec><sec><title>Risk factors for the epidemic process COVID-19 / Факторы риска развития эпидемического процесса COVID-19</title><p>The pathogenic coronavirus SARS-CoV-2 has paralyzed all human activities around the world, making it impossible to resolve the global health and economic crisis. The number of confirmed infected cases was growing every day and rising in the next fifth wave [<xref ref-type="bibr" rid="cit6">6</xref>]. Decisions about the course of each epidemic are based on an analysis of statistics on circulating infection in the population over the period described. Epidemiologists, infectious disease specialists, clinicians, and other experts analyze primarily the risks of an epidemic (pandemic) and their factors [<xref ref-type="bibr" rid="cit5">5</xref>][8–17][27–29]. The following available sources differentiate or assess risk factors for severity or mortality from COVID-19 [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit7">7</xref>].</p><p>The elevated mortality rate among high-incomed patients suffering from COVID-19 has been unexpectedly recognized [<xref ref-type="bibr" rid="cit12">12</xref>][<xref ref-type="bibr" rid="cit29">29</xref>]. A similar trend was found in statistical populations of continents [<xref ref-type="bibr" rid="cit28">28</xref>].</p><p>Africa is characterized by a low standard of living: gross domestic product is 32 times, consumption of high-calorie foods is 2.2 times, protein intake is 1.6 times lower than in NA [<xref ref-type="bibr" rid="cit30">30</xref>][<xref ref-type="bibr" rid="cit31">31</xref>]. In Africa the RPr was 18 times and the IFR 22 times lower than in NA [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit15">15</xref>][<xref ref-type="bibr" rid="cit28">28</xref>]. This difference between NA and Asia was less contrasting (Fig. 1) but also significant; accordingly, the infection fatality rate (IFR) and rate of prevalence (RPr) were several times lower in Asia, than in NA [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit28">28</xref>].</p><p>It was investigated the influence of socio-economic factors on the pathogenesis of the virus and shown that the level of consumption of fats and total protein could be a reliable factor influencing the pathogenesis of the SARS-CoV-2 virus [<xref ref-type="bibr" rid="cit28">28</xref>]. In the non-white (black and South-Asian) groups in the USA or Great Britain population, the rates of incidence and mortality were higher than in the white group [<xref ref-type="bibr" rid="cit11">11</xref>][<xref ref-type="bibr" rid="cit12">12</xref>][<xref ref-type="bibr" rid="cit16">16</xref>]. These studies supported the idea that eating habits rather than ethnicity were the risk factors for COVID-19.</p></sec><sec><title>Relation between dietary habits and progress of SARS-COV-2 infection / Связь между пищевыми привычками и развитием инфекции SARS-COV-2</title><p>Many publications and reviews have suggested that a person’s diet plays an important role in the development of COVID-19 outcomes [34–42]. For a long time, nutritionists believe that an optimal diet helps in the fight against diseases, including infectious ones, since proper nutrition improves the immune system and strengthens the body’s defenses [<xref ref-type="bibr" rid="cit34">34</xref>][40–43]. Nutritional deficiencies and low metabolic rates have been suggested to exacerbate the disease and increase mortality [<xref ref-type="bibr" rid="cit34">34</xref>][<xref ref-type="bibr" rid="cit36">36</xref>][<xref ref-type="bibr" rid="cit38">38</xref>][<xref ref-type="bibr" rid="cit44">44</xref>]. Therefore, patients with COVID-19 were recommended, an enriched diet with all essential nutrients, vitamins, and minerals [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit38">38</xref>][<xref ref-type="bibr" rid="cit40">40</xref>][<xref ref-type="bibr" rid="cit44">44</xref>][<xref ref-type="bibr" rid="cit45">45</xref>]. It was suggested, that a Mediterranean diet could reduce the risk of severe SARS-CoV-2 disease and COVID-19 mortality [<xref ref-type="bibr" rid="cit46">46</xref>]. Several studies have shown that COVID-19 disease was worsening not only due to malnutrition, but also due to obesity [35–39]. To combat the infectious COVID-19 disease, excessive consumption of fatty and protein foods was recommended [<xref ref-type="bibr" rid="cit40">40</xref>]. Opposite assumptions were the following: a plant-based diet was beneficial for recovery from COVID-19 [<xref ref-type="bibr" rid="cit47">47</xref>] and the severity of the development of the epidemic process of SARS-CoV-2 in humans directly depends on the amount of fat and protein consumed, as has been shown for populations of continents and different regions [<xref ref-type="bibr" rid="cit28">28</xref>].</p><p>Proteins are vital macronutrients for the animal body. People get animal and plant proteins from food. On the continents of Asia and Africa, plant food (Fig. 1) predominates (66% and 76% of the total protein, respectively). Nations in Europe and America consumed more fat and protein than in Asia or Africa for decades (Fig. 1), and this is also much more than the WHO recommendation [<xref ref-type="bibr" rid="cit43">43</xref>][<xref ref-type="bibr" rid="cit48">48</xref>]. The diet of Europeans and North Americans is dominated by animal proteins (58 and 68 g/person/day), namely 57% of the total protein consumed.</p><fig id="fig-1"><caption><p>Figure 1. Relation between outcomes of the COVID-19 pandemic and diet factors on five continents (compiled by the author). Correlation between rate of prevalence (RPr), infection fatality rate (IFR) or case fatality rate (CFR) of the SARS-CoV-2 infection and amount of consumed animal protein (AP), plant protein (PP), whole protein (wP) or sugar (Sug). AP, PP, wP – in protein g/day/person [31], Sugar – in Kg/year/capita [32], RPr – total amount infected/1000 population (as of June 10, 2021) [6], IFR – total amount deaths/50 000 population (as of June 10, 2021), CFR – relative mortality in %. World Health Organization recommendation: maximum 50 g sugar and its products per day per capita [33]Рисунок 1. Связь между последствиями пандемии COVID-19 и факторами питания на пяти континентах (составлено автором). Корреляция между уровнем распространенности (англ. rate of prevalence, RPr) и смертности (англ. infection fatality rate, IFR) или относительной летальности (англ. case fatality rate, CFR) от инфекции SARS-CoV-2 и количеством потребляемого животного белка (англ. animal protein, AP), растительного белка (англ. plant protein, PP), общего белка (англ. whole protein, wP) или сахара (англ. sugar, Sug). Белки – г/сут на человека [31], сахар – кг/год на душу населения [32], RPr – общее количество инфицированных на 1 тыс. населения (на 10.06.2021) [6], IFR – общее количество смертей на 50 тыс. населения (на 10.06.2021), CFR – относительная летальность в %. Рекомендация Всемирной организации здравоохранения: не более 50 г сахара и продуктов его переработки в день на душу населения [33]</p></caption><graphic xlink:href="farmaec-15-4-g001.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/farmaec/2022/4/awOC5sIw19VCbSO6bxhK3CfGlbXMI1AVUFmY0zNE.jpeg</uri></graphic></fig><p>Inhabitants of Africa consume 4.2 times and Asia 2.6 times less animal protein than in NA. At the same time, the maximum difference in the amount of vegetable protein consumed by a person on different continents ranges from 25% to 30% (in NA 41, in Asia 51, and Africa 53 g/day). People in some Asian countries consume less fat, and in Africa, much less protein than the WHO recommendation [<xref ref-type="bibr" rid="cit43">43</xref>][<xref ref-type="bibr" rid="cit48">48</xref>]. The inhabitants of these two continents consume significantly less animal protein than the world average. Fig.1 shows a direct association between RPr or IFR on five continents and the amount of animal protein consumed, with correlation coefficients r=0.92 for incidence or r=0.8 for mortality. These correlation coefficients for total protein were smaller: 0.84 or 0.69, respectively, for the same continents (Fig. 1) [<xref ref-type="bibr" rid="cit28">28</xref>]. All indicators of SARS-CoV-2 for continents: RPr, IFR, and case fatality rate (CFR) show a higher correlation for vegetable protein than for animal protein with r=–0.98, r=–0.98, and r=–0.49. The correlation between the severity of COVID-19 and the amount of plant or animal proteins eaten is more pronounced (Fig. 1) than between total dietary protein [<xref ref-type="bibr" rid="cit28">28</xref>]. A direct correlation between the level of manifestation of viral pathogenesis and the consumed quantity of plant proteins on the continents was obtained for both RPr and IFR (Fig. 1).</p><p>A similar analysis was carried out for the selected groups of countries [<xref ref-type="bibr" rid="cit28">28</xref>] on each continent. It was analyzed the epidemiological data of grouped countries from each continent, and the relationship presented for most of these countries: lower consumption of fat and total protein correlates with less severe pathogenicity of the SARS-CoV-2 [<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit47">47</xref>]. A side effect of COVID-19 is an increase in plasma cholesterol in patients [<xref ref-type="bibr" rid="cit49">49</xref>]. A diet rich in fat amplifies the circulating ACE [<xref ref-type="bibr" rid="cit50">50</xref>], which explains the positive correlation between fat intake and RPr or IFR of COVID-19 [<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit51">51</xref>]. Here, the same groups of countries [<xref ref-type="bibr" rid="cit28">28</xref>] have used to analyze risk factors for infection with SARS-CoV-2 (Fig. 2).</p><fig id="fig-2"><caption><p>Figure 2. Relation between outcomes of the COVID-19 pandemic and diet factors in different country groups of five continents (compiled by the author). Correlation between rate of prevalence (RPr), infection fatality rate (IFR) or case fatality rate (CFR) of the SARS-CoV-2 infection and amount of consumed animal protein (AP), plant protein (PP), whole protein (wP) or sugar (Sug). AP, PP, wP – in protein g/day/person, sugar – in Kcal/day/capita [31], RPr – total amount infected/1000 population (as of June 10, 2021) [6], IFR – total amount deaths/50 000 population (as of June 10, 2021), CFR – relative mortality in %. On abscissa axis are names of country groups taken from [28]: USA – United States of America; SIP – Spain, Italy, Portugal (Mediterranean Europe); WE – Western Europe (Austria, Belgium, France, Germany, Netherlands, Switzerland); RUB – Russia, Ukraine, Belarus (Eastern Europe); BBP – Bolivia, Brasil, Paraquay (North-West of Southern America); СEP – Colombia, Ecuador, Peru (South-East of Southern America); KUT – Kyrgyzstan, Uzbekistan, Tajikistan (Central Asia); CLTV – Cambodia, Laos, Thailand, Vietnam (Mainland South-Estern Asia); MIP – Malaysia, Indonesia, Philippines (Maritimeland South-Estern Asia); BINP – Bangladesh, India, Nepal, Pakistan (South Asia); ESE – Egipt, Ethiopia, Sudan (North Nile region); BNS – Botswana, Namibia, South Africa (Southern Africa); BNN – Benin, Niger, Nigeria (Eastern part of West Africa)Рисунок 2. Связь между последствиями пандемии COVID-19 и факторами питания в различных группах стран пяти континентов (составлено автором). Корреляция между уровнем распространенности (англ. rate of prevalence, RPr) и смертности (англ. infection fatality rate, IFR) или относительной летальности (англ. case fatality rate, CFR) от инфекции SARS-CoV-2 и количеством потребляемого животного белка (англ. animal protein, AP), растительного белка (англ. plant protein, PP), общего белка (англ. whole protein, wP) или сахара (англ. sugar, Sug). Белки – г/сут на человека, сахар – ккал/сут на человека [31], RPr – общее количество инфицированных на 1 тыс. населения (на 10.06.2021) [6], IFR – общее количество смертей на 50 тыс. населения (на 10.06.2021), CFR – относительная летальность в %. По оси абсцисс приведены названия групп стран [28]: США – Соединенные Штаты Америки; SIP (англ. Spain, Italy, Portugal) – Испания, Италия, Португалия (Средиземноморская Европа); WE (англ. Western Europe) – Западная Европа (Австрия, Бельгия, Франция, Германия, Нидерланды, Швейцария); RUB (англ. Russia, Ukraine, Belarus) – Россия, Украина, Беларусь (Восточная Европа); BBP (англ. Bolivia, Brasil, Paraquay) – Боливия, Бразилия, Парагвай (северо-запад Южной Америки); СEP (англ. Colombia, Ecuador, Peru) – Колумбия, Эквадор, Перу (юго-восток Южной Америки); KUT (англ. Kyrgyzstan, Uzbekistan, Tajikista) – Кыргызстан, Узбекистан, Таджикистан (Центральная Азия); CLTV (англ. Cambodia, Laos, Thailand, Vietnam) – Камбоджа, Лаос, Таиланд, Вьетнам (материковая часть Юго-Восточной Азии); MIP (англ. Malaysia, Indonesia, Philippines) – Малайзия, Индонезия, Филиппины (приморская часть Юго-Восточной Азии); BINP (англ. Bangladesh, India, Nepal, Pakistan) – Бангладеш, Индия, Непал, Пакистан (Южная Азия); ESE (англ. Egipt, Ethiopia, Sudan) – Египет, Эфиопия, Судан (регион Северного Нила); BNS (англ. Botswana, Namibia, South Africa) – Ботсвана, Намибия, Южная Африка (юг Африки); BNN (англ. Benin, Niger, Nigeria) – Бенин, Нигер, Нигерия (восточная часть Западной Африки)</p></caption><graphic xlink:href="farmaec-15-4-g002.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/farmaec/2022/4/e13CfKmenAuQ5oVvEKZ4tnsZqkJ1Ta2a0Fvt2NXK.jpeg</uri></graphic></fig><p>The tendency of the dependence of the severity of COVID-19 on the amount of consumed animal proteins revealed for the continents (Fig. 1) also manifests itself (Fig. 2) for the previously selected groups of countries [<xref ref-type="bibr" rid="cit28">28</xref>]. In Ethiopia and Nigeria, from ESE and BNN groups (Fig. 2), the population consumes 12 and 10 times less animal-based protein than in the USA, and, accordingly, the frequency of infection with the virus was 44 and 129 times lower. In addition, inhabitants of these two African countries consume 7.5 and 5.6 times less sugar than residents of the USA (Fig. 2). In countries with low consumption of sugar and its derivatives, the incidence of SARS-CoV-2 virus infection was usually lower. The correlation coefficients of the dependence of RPr or IFR on the amount of sugar eaten were for selected groups 0.8 or 0.7 respectively (Fig. 2). To reduce the risk of glucose in COVID-19 development, recommended the use of non-physiological glucose analogues for therapy. A review by F. Paoli et al. suggested that elevated blood glucose suppresses the antiviral response, and stimulates the expression of ACE2 receptors in animal tissues, increasing the severity of COVID-19 [<xref ref-type="bibr" rid="cit52">52</xref>]. The trend in the severity of COVID-19 across country groups matches the consumption of both animal-based protein and sugar with its derivatives (Fig. 2).</p><p>Although there may be exceptions in the correlation for some countries, in which, in the short period before the study day of the pandemic, the number of infected patients increased sharply due to the penetration of new variants of the SARS-CoV-2 virus with very high infectivity. So has happened in May and June of this year in Peru, Brazil, and India [5–7]. At the end of April 2021, such a phenomenon was recorded in a group of Central European countries (Czech, Poland, and Slovak Republics) [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit28">28</xref>], whose residents consume less fat, sugar, and animal proteins [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit48">48</xref>] but the data on infection and mortality rates (RPr and IFR) were significantly higher than in neighboring West-Europe [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit28">28</xref>]. In the South Africa Republic, also in the BBP and CEP groups from Southern America, in contrast to other countries, mortality jumped out of the trend of dependence on the amount of fat and protein consumed. In these countries, the escalation of the pathogenic process of the SARS-CoV-2 virus may be influenced by more contagious of the virus variants (Beta- and Gamma) [<xref ref-type="bibr" rid="cit5">5</xref>][<xref ref-type="bibr" rid="cit7">7</xref>]. The influence of dietary factors on the number and rate of transmission of virions, or the basic reproduction number (Ro), should be principal minimal.</p></sec><sec><title>Regional diets and pathogenic effects of the SARS-COV-2 Coronavirus / Региональные диеты и патогенные эффекты коронавируса SARS-COV-2</title><p>The other two country groups, RUB (Russia, Ukraine, Belarus) and CLTV (Cambodia, Laos, Thailand, Vietnam), were well outside the trend line in terms of the rates of infections (RPr) or deaths (IFR) (Fig. 2). In the countries of these two groups, people consume less protein and fat than Europeans [<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit47">47</xref>]; moreover, the intervals between waves of infection were much longer than the world average [<xref ref-type="bibr" rid="cit6">6</xref>]. Thus, in the RUB group, the numbers of RPr and IFR were 70% and 55% of the average data for Europe.</p><p>In the CLTV region, RPr and IFR values were extremely lower than the average for Asia (928 and 6 per million, respectively) [<xref ref-type="bibr" rid="cit6">6</xref>], although the inhabitants of this region consume fats and animal proteins, almost equal to the average for Asian continent [<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit48">48</xref>]. The consumption of sugars in this group is not lower than [<xref ref-type="bibr" rid="cit32">32</xref>][<xref ref-type="bibr" rid="cit33">33</xref>][<xref ref-type="bibr" rid="cit48">48</xref>] in other regions of Asia (Fig. 2).</p><p>The diet in the CLTV region is plant-based with a high consumption of soy products (Table 1). The average world consumption of soybeans is 0.77 g/day/person [<xref ref-type="bibr" rid="cit48">48</xref>]. Thus, in Vietnam with a high population density (314 people/sq. Km) [<xref ref-type="bibr" rid="cit30">30</xref>][<xref ref-type="bibr" rid="cit31">31</xref>] the incidence of coronavirus infection and mortality were among the lowest in the world (Fig. 1, 2; Table 1). In this state, residents consume the largest amount of soy protein per capita (9.14 g per day) [<xref ref-type="bibr" rid="cit48">48</xref>]. Also, in Taiwan, with its very high population density (673 persons/sq. Km [<xref ref-type="bibr" rid="cit30">30</xref>][<xref ref-type="bibr" rid="cit31">31</xref>]), infection and mortality rates were among the lowest in Asia [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit28">28</xref>]. The inhabitants of this island eat about 8 g of soy protein per day.</p><fig id="fig-3"><caption><p>Table 1. Diet factors and the outcomes of COVID-19 in South- and South-East Asia countries (compiled by the author)Таблица 1. Факторы диеты и последствия COVID-19 в странах Южной и Юго-Восточной Азии (составлено автором)</p><p>Note. RPr – rate of prevalence; IFR – infection fatality rate; Soy – soy protein; AP – animal protein; PP – plant protein; F – fat; Sug – sugar. Soy, AP, PP, F – in g/day/person [31], Soy/AP – in %, Sug – in Kg/year/capita [32]. RPr – total amount infected/1mln population (as of June 10, 2021) [6]; IFR – total amount deaths/1mln population (as of June 10, 2021).Примечание. RPr (англ. rate of prevalence) – уровень распространенности; IFR (англ. infection fatality rate) – уровень смертности; Soy (англ. soy protein) – соевый белок; AP (англ. animal protein) – животные белки; PP (англ. plant protein) – растительные белки; F (англ. fat) – жиры; Sug (англ. sugar) – сахар. Белки и жиры – г/сут на человека [31], Soy/AP – %, сахар – кг/год на душу населения [32]. RPr – общее количество инфицированных на 1 тыс. населения (на 10.06.2021) [6]; общее количество смертей на 50 тыс. населения (на 10.06.2021).</p></caption><graphic xlink:href="farmaec-15-4-g003.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/farmaec/2022/4/O7Ouj2SbcCQiUhacueZNQSCShJO43vQRmiEfome2.jpeg</uri></graphic></fig><p>Despite the high heterogeneity of data in the group of Asian countries with high consumption of soybeans, the revealed relationship between the consumption of plant proteins and RPr or IFR remains higher than for fat, sugar, or animal proteins.</p><p>The Asian population, which consumes a lot of soy products, has the lowest infection rate not only in the world but also in Asia (Fig. 1, 2), even with high consumption of fatty or protein foods and a very high population density [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit30">30</xref>][<xref ref-type="bibr" rid="cit48">48</xref>]. There was no relationship between RPr or IFR and level of consumption of fat, sugar, and soy in these countries (Table 2), which have been easy throughout the COVID-19 pandemic [<xref ref-type="bibr" rid="cit6">6</xref>]. This reason for the very mild outcomes of the SARSCoV- 2 coronavirus needs to investigate. Soybeans contain a wide variety of serine and other proteases inhibitors, the activity of which was minimally reduced after prolonged boiling [53–55]. Are soybeans virucidal or food protease inhibitors able to disrupt the activity of viral enzymes important for the infectious process? The question of whether soy products help to block the development of the SARS-CoV-2 virus can be resolved after serious research.</p><fig id="fig-4"><caption><p>Table 2. Pearson correlation coefficients (r) between COVID-19 outcomes and different food components in South- and South-East Asia countries (compiled by the author)Таблица 2. Коэффициенты корреляции Пирсона (r) между последствиями COVID-19 и различными компонентами питания в странах Южной и Юго-Восточной Азии (составлено автором)</p><p>Note. wP – whole protein; AP – animal protein; PP – plant protein; F – fat; Sug – sugar; Soy – soy protein; RPr – rate of prevalence; IFR – infection fatality rate. Correlation coefficients were calculated from data in the Table 1.Примечание. wP (англ. whole protein) – общий белок; AP (англ. animal protein) – животные белки; PP (англ. plant protein) – растительные белки; Sug (англ. sugar) – сахар; Soy (англ. soy protein) – соевый белок; RPr (англ. rate of prevalence) – уровень распространенности; IFR (англ. infection fatality rate) – уровень смертности. Коэффициенты корреляции рассчитаны на основе данных, приведенных в таблице 1.</p></caption><graphic xlink:href="farmaec-15-4-g004.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/farmaec/2022/4/b2sk5f4kPJCDv9tlCw6ExX7ZVgf0z3bsf8V1T7uY.jpeg</uri></graphic></fig><p>The RUB group has the lowest population density in the selected Europe clusters [<xref ref-type="bibr" rid="cit6">6</xref>][<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit30">30</xref>]. In the countries of this group, RPr was much lower, and IFR was slighter than the European average (Fig. 1, 2). In this RUB region, residents consume less fat and protein than other Europeans [<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit48">48</xref>]; however, the largest amount of potatoes in the world (6.17 g of protein per day per capita, or 13.4% of plant proteins eaten). In Belarus, on average, each inhabitant intakes 8 g of potato proteins per day, or 18.6% of all consumed vegetable proteins [<xref ref-type="bibr" rid="cit28">28</xref>][<xref ref-type="bibr" rid="cit48">48</xref>]. This country had the lowest rates of both infection (RPr) and mortality (IFR) from COVID-19, not only in Europe, but also in the group [<xref ref-type="bibr" rid="cit6">6</xref>]. Potatoes and soy are similar in protease inhibitors producing and digestion affecting, and uptake of nutrients in the gastrointestinal tract. Potato tubers contain a wide range of different protease inhibitors with mass variations of 5–160 KDa. Potatoes synthesize a large amount of protease inhibitors which are relatively thermostable and have low Ki [55–57]. Interested researchers should investigate whether potato products can directly suppress infection or reduce the severity of COVID-19 disease.</p><p>In traditional medicine, especially in Asian countries, numerous herbs or natural remedies are widely used to fight various infections, including Coronavirus [<xref ref-type="bibr" rid="cit55">55</xref>][<xref ref-type="bibr" rid="cit58">58</xref>][<xref ref-type="bibr" rid="cit59">59</xref>]. The structure and mechanism of action of different synthetic inhibitors of viral proteases are known [<xref ref-type="bibr" rid="cit55">55</xref>][<xref ref-type="bibr" rid="cit58">58</xref>], and the role and anti-viral effect of other components have been analyzed [<xref ref-type="bibr" rid="cit49">49</xref>][<xref ref-type="bibr" rid="cit55">55</xref>][60–63]. In light of these studies, the effect of plant foods should be investigated.</p></sec><sec><title>CONCLUSION / ЗАКЛЮЧЕНИЕ</title><p>After 15 months of the COVID-19 pandemic, the global community has learned some key lessons. A quantitative analysis was carried out, using large statistical samples, of the influence of the staple food components on the development of infection with the SARS-CoV-2 virus and the severity of the COVID-19 disease. A direct correlation was found between the severity of the development of COVID-19 and the quantity of dietary proteins, fats and sugars consumed.</p><p>Analysis using big epidemic data showed that in the case with the minimum rate of SARS-CoV-2 pathogenic outcomes, the level of ingested fats, sugars, and proteins of animal origin was low or not significantly higher than the WHO recommended. Countries with high consumption of soy or potato products had lower morbidity and mortality rates from COVID-19 than neighbors. A high intake of plant-based proteins was correlated with low severity of COVID-19. Perhaps, not only soy or potatoes, but also other dietary vegetables contain substances to help an organism resist pathogens, including the SARS-CoV-2 virus.</p><p>The established relationship between nutritional factors and the outcomes of SARS-CoV-2 infection requires detailed study. The overconsumption of essential nutrients may not be critical to the stages of transmission of infection, but to remove the reproduction of the Coronavirus. From the publications cited and this analysis of statistical data, it follows that the type of diet may be a decisive factor in development of the COVID-19 pathogenesis. Consequently, a specific recommendation arises to combat the pandemic. Models of national food-based dietary guidelines need to be developed.</p><p>The nature of found effects of dietary factors on the host-pathogen interaction should be proved by methods of nutritional biochemistry and molecular biology of metabolism.</p><p>Research using modern methods will help identify dietary components that can inhibit the replication cycle of the pathogenic SARS-CoV-2 virus. Establishing the nature and molecular structure of the antiviral factor will help in the rapid creation of the required etiotropic therapeutic agent.</p><p>1. https://www.who.int.
2. https://www.worldometers.info.
3. http://www.fao.org.
4. https://ourworldindata.org.
5. https://databank.worldbank.org.
6. https://www.imf.org.
</p></sec></body><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">WHO Director-General's opening remarks at the media briefing on COVID-19 – 11 March 2020. Available at: https://www.who.int/directorgeneral/speeches/detail/who-director-general-s-opening-remarks-atthe-media-briefing-on-covid-19---11-march-2020 (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">WHO Director-General's opening remarks at the media briefing on COVID-19 – 11 March 2020. Available at: https://www.who.int/directorgeneral/speeches/detail/who-director-general-s-opening-remarks-atthe-media-briefing-on-covid-19---11-march-2020 (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Hu B., Guo H., Zhou P., et al. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 2021; 19 (3): 141–54. https://doi.org/10.1038/s41579-020-00459-7.</mixed-citation><mixed-citation xml:lang="en">Hu B., Guo H., Zhou P., et al. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 2021; 19 (3): 141–54. https://doi.org/10.1038/s41579-020-00459-7.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">To K.K., Sridhar S., Chiu K.H., et al. Lessons learned 1 year after SARS-CoV-2 emergence leading to COVID-19 pandemic. Emerg Microbes Infect. 2021; 10 (1): 507–35. https://doi.org/10.1080/22221751.2021.1898291.</mixed-citation><mixed-citation xml:lang="en">To K.K., Sridhar S., Chiu K.H., et al. Lessons learned 1 year after SARS-CoV-2 emergence leading to COVID-19 pandemic. Emerg Microbes Infect. 2021; 10 (1): 507–35. https://doi.org/10.1080/22221751.2021.1898291.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">V’kovski P., Kratzel A., Steiner S., et al. Coronavirus biology and replication: implications for SARS-CoV-2. Nat Rev Microbiol. 2021; 19 (3): 155–70. https://doi.org/10.1038/s41579-020-00468-6.</mixed-citation><mixed-citation xml:lang="en">V’kovski P., Kratzel A., Steiner S., et al. Coronavirus biology and replication: implications for SARS-CoV-2. Nat Rev Microbiol. 2021; 19 (3): 155–70. https://doi.org/10.1038/s41579-020-00468-6.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Coronavirus disease (COVID-19) pandemic. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">Coronavirus disease (COVID-19) pandemic. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Worldometer. Coronavirus Updates. Available at: https://www.worldometers.info (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">Worldometer. Coronavirus Updates. Available at: https://www.worldometers.info (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Centers for Disease Control Prevention. COVID-19. Understanding risk. Available at: https://www.cdc.gov/coronavirus/2019-ncov/coviddata/investigations-discovery/assessing-risk-factors.html (accessed 20.08.2022).</mixed-citation><mixed-citation xml:lang="en">Centers for Disease Control Prevention. COVID-19. Understanding risk. Available at: https://www.cdc.gov/coronavirus/2019-ncov/coviddata/investigations-discovery/assessing-risk-factors.html (accessed 20.08.2022).</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Geng M.J., Wang L.P., Ren X., et al. Risk factors for developing severe COVID-19 in China: an analysis of disease surveillance data. Infect Dis Poverty. 2021; 10 (1): 48. https://doi.org/10.1186/s40249-021-00820-9.</mixed-citation><mixed-citation xml:lang="en">Geng M.J., Wang L.P., Ren X., et al. Risk factors for developing severe COVID-19 in China: an analysis of disease surveillance data. Infect Dis Poverty. 2021; 10 (1): 48. https://doi.org/10.1186/s40249-021-00820-9.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Booth A., Reed A.B., Ponzo S., et al. Population risk factors for severe disease and mortality in COVID19: a global systematic review and metaanalysis. PLoS One. 2021; 16 (3): e0247461. https://doi.org/10.1371/journal.pone.0247461.</mixed-citation><mixed-citation xml:lang="en">Booth A., Reed A.B., Ponzo S., et al. Population risk factors for severe disease and mortality in COVID19: a global systematic review and metaanalysis. PLoS One. 2021; 16 (3): e0247461. https://doi.org/10.1371/journal.pone.0247461.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Jin J., Agarwala N., Kundu P., et al. Individual and community-level risk for COVID-19 mortality in the United States. Nat Med. 2021; 27 (2): 264–9. https://doi.org/10.1038/s41591-020-01191-8.</mixed-citation><mixed-citation xml:lang="en">Jin J., Agarwala N., Kundu P., et al. Individual and community-level risk for COVID-19 mortality in the United States. Nat Med. 2021; 27 (2): 264–9. https://doi.org/10.1038/s41591-020-01191-8.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Mathur R., Rentsch C.T., Morton C.E., et al. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet. 2021; 397 (10286): 1711–24. https://doi.org/10.1016/S0140-6736(21)00634-6.</mixed-citation><mixed-citation xml:lang="en">Mathur R., Rentsch C.T., Morton C.E., et al. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet. 2021; 397 (10286): 1711–24. https://doi.org/10.1016/S0140-6736(21)00634-6.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Roy S., Ghosh P. Factors affecting COVID-19 infected and death rates inform lockdown-related policymaking. PLoS One. 2020; 15 (10): e0241165. https://doi.org/10.1371/journal.pone.0241165.</mixed-citation><mixed-citation xml:lang="en">Roy S., Ghosh P. Factors affecting COVID-19 infected and death rates inform lockdown-related policymaking. PLoS One. 2020; 15 (10): e0241165. https://doi.org/10.1371/journal.pone.0241165.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Tan A.X., Hinman J.A., Abdel Magid H.S., et al. Association between income inequality and county-level COVID-19 cases and deaths in the US. JAMA Netw Open. 2021; 4 (5): e218799. https://doi.org/10.1001/jamanetworkopen.2021.8799.</mixed-citation><mixed-citation xml:lang="en">Tan A.X., Hinman J.A., Abdel Magid H.S., et al. Association between income inequality and county-level COVID-19 cases and deaths in the US. JAMA Netw Open. 2021; 4 (5): e218799. https://doi.org/10.1001/jamanetworkopen.2021.8799.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Van Damme W., Dahake R., Delamou A., et al. The COVID-19 pandemic: diverse contexts; different epidemics-how and why? BMJ Glob Health. 2020; 5 (7): e003098. https://doi.org/10.1136/bmjgh-2020-003098.</mixed-citation><mixed-citation xml:lang="en">Van Damme W., Dahake R., Delamou A., et al. The COVID-19 pandemic: diverse contexts; different epidemics-how and why? BMJ Glob Health. 2020; 5 (7): e003098. https://doi.org/10.1136/bmjgh-2020-003098.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Wamai R.G., Hirsch J.L., Van Damme W., et al. What could explain the lower COVID-19 burden in Africa despite considerable circulation of the SARS-CoV-2 virus? Int J Environ Res Public Health. 2021; 18 (16): 8638. https://doi.org/10.3390/ijerph18168638.</mixed-citation><mixed-citation xml:lang="en">Wamai R.G., Hirsch J.L., Van Damme W., et al. What could explain the lower COVID-19 burden in Africa despite considerable circulation of the SARS-CoV-2 virus? Int J Environ Res Public Health. 2021; 18 (16): 8638. https://doi.org/10.3390/ijerph18168638.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Williamson E.J., Walker A.J., Bhaskaran K., et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020; 584 (7821): 430–6. https://doi.org/10.1038/s41586-020-2521-4.</mixed-citation><mixed-citation xml:lang="en">Williamson E.J., Walker A.J., Bhaskaran K., et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020; 584 (7821): 430–6. https://doi.org/10.1038/s41586-020-2521-4.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang W., Zhang C., Bi Y., et al. Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model. Results Phys. 2021; 22: 103881. https://doi.org/10.1016/j.rinp.2021.103881.</mixed-citation><mixed-citation xml:lang="en">Zhang W., Zhang C., Bi Y., et al. Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model. Results Phys. 2021; 22: 103881. https://doi.org/10.1016/j.rinp.2021.103881.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Abdelrahman Z., Li M., Wang X. Comparative Review of SARS‑CoV-2, SARS-CoV, MERS-CoV, and Influenza A respiratory viruses. Front Immunol. 2020; 11: 552909. https://doi.org/10.3389/fimmu.2020.552909.</mixed-citation><mixed-citation xml:lang="en">Abdelrahman Z., Li M., Wang X. Comparative Review of SARS‑CoV-2, SARS-CoV, MERS-CoV, and Influenza A respiratory viruses. Front Immunol. 2020; 11: 552909. https://doi.org/10.3389/fimmu.2020.552909.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Hoffmann M., Kleine-Weber H., Schroeder S., et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020; 181 (2): 271–80.e8. https://doi.org/10.1016/j.cell.2020.02.052.</mixed-citation><mixed-citation xml:lang="en">Hoffmann M., Kleine-Weber H., Schroeder S., et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020; 181 (2): 271–80.e8. https://doi.org/10.1016/j.cell.2020.02.052.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Wu S.C., Arthur C.M., Wang J., et al. The SARS-CoV-2 receptorbinding domain preferentially recognizes blood group A. Blood Adv. 2021; 5 (5): 1305–9. https://doi.org/10.1182/bloodadvances.2020003259.</mixed-citation><mixed-citation xml:lang="en">Wu S.C., Arthur C.M., Wang J., et al. The SARS-CoV-2 receptorbinding domain preferentially recognizes blood group A. Blood Adv. 2021; 5 (5): 1305–9. https://doi.org/10.1182/bloodadvances.2020003259.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Mokhtari T., Hassani F., Ghaffari N., et al. COVID-19 and multiorgan failure: a narrative review on potential mechanisms. J Mol Histol. 2020; 51 (6): 613–28. https://doi.org/10.1007/s10735-020-09915-3.</mixed-citation><mixed-citation xml:lang="en">Mokhtari T., Hassani F., Ghaffari N., et al. COVID-19 and multiorgan failure: a narrative review on potential mechanisms. J Mol Histol. 2020; 51 (6): 613–28. https://doi.org/10.1007/s10735-020-09915-3.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Kordzadeh-Kermani E., Khalili H., Karimzadeh I. Pathogenesis, clinical manifestations and complications of coronavirus disease 2019 (COVID-19). Future Microbiol. 2020; 15: 1287–305. https://doi.org/10.2217/fmb-2020-0110.</mixed-citation><mixed-citation xml:lang="en">Kordzadeh-Kermani E., Khalili H., Karimzadeh I. Pathogenesis, clinical manifestations and complications of coronavirus disease 2019 (COVID-19). Future Microbiol. 2020; 15: 1287–305. https://doi.org/10.2217/fmb-2020-0110.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Al-Aly Z., Xie Y., Bowe B. High-dimensional characterization of postacute sequelae of COVID-19. Nature. 2021; 594 (7862): 259–64. https://doi.org/10.1038/s41586-021-03553-9.</mixed-citation><mixed-citation xml:lang="en">Al-Aly Z., Xie Y., Bowe B. High-dimensional characterization of postacute sequelae of COVID-19. Nature. 2021; 594 (7862): 259–64. https://doi.org/10.1038/s41586-021-03553-9.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Sudre C.H., Murray B., Varsavsky T., et al. Attributes and predictors of long COVID. Nat Med. 2021; 27 (4): 626–31. https://doi.org/10.1038/s41591-021-01292-y.</mixed-citation><mixed-citation xml:lang="en">Sudre C.H., Murray B., Varsavsky T., et al. Attributes and predictors of long COVID. Nat Med. 2021; 27 (4): 626–31. https://doi.org/10.1038/s41591-021-01292-y.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Karlinsky A., Kobak D. Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset. Elife. 2021; 10: e69336. https://doi.org/10.7554/eLife.69336.</mixed-citation><mixed-citation xml:lang="en">Karlinsky A., Kobak D. Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset. Elife. 2021; 10: e69336. https://doi.org/10.7554/eLife.69336.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Fan J., Han F., Liu H. Challenges of Big Data analysis. Natl Sci Rev. 2014; 1 (2): 293–314. https://doi.org/10.1093/nsr/nwt032.</mixed-citation><mixed-citation xml:lang="en">Fan J., Han F., Liu H. Challenges of Big Data analysis. Natl Sci Rev. 2014; 1 (2): 293–314. https://doi.org/10.1093/nsr/nwt032.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Kontis V., Bennett J.E., Rashid T., et al. Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries. Nat Med. 2020; 26 (12): 1919–28. https://doi.org/10.1038/s41591-020-1112-0.</mixed-citation><mixed-citation xml:lang="en">Kontis V., Bennett J.E., Rashid T., et al. Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries. Nat Med. 2020; 26 (12): 1919–28. https://doi.org/10.1038/s41591-020-1112-0.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Ponomarenko S. Economic and social factors affecting the epidemiological process of the SARS-CoV-2 coronavirus. Available at: https://doi.org/10.21055/preprints-3111965 (accessed 20.08.2022).</mixed-citation><mixed-citation xml:lang="en">Ponomarenko S. Economic and social factors affecting the epidemiological process of the SARS-CoV-2 coronavirus. Available at: https://doi.org/10.21055/preprints-3111965 (accessed 20.08.2022).</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Hashim M.J., Alsuwaidi A.R., Khan G. Population risk factors for COVID-19 mortality in 93 countries. J Epidemiol Glob Health. 2020; 10 (3): 204–8. https://doi.org/10.2991/jegh.k.200721.001.</mixed-citation><mixed-citation xml:lang="en">Hashim M.J., Alsuwaidi A.R., Khan G. Population risk factors for COVID-19 mortality in 93 countries. J Epidemiol Glob Health. 2020; 10 (3): 204–8. https://doi.org/10.2991/jegh.k.200721.001.</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">World Bank Open Data. Available at: https://data.worldbank.org/ (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">World Bank Open Data. Available at: https://data.worldbank.org/ (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Our World in Data. Research and data to make progress against the world’s largest problems. Available at: https://ourworldindata.org (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">Our World in Data. Research and data to make progress against the world’s largest problems. Available at: https://ourworldindata.org (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">World per Capita Consumption of Sugar, 2012 to 2018. Available at: https://www.indiansugar.com/PDFS/World_per_Capita_Consumption_of_Sugar.pdf (accessed 20.08.2022).</mixed-citation><mixed-citation xml:lang="en">World per Capita Consumption of Sugar, 2012 to 2018. Available at: https://www.indiansugar.com/PDFS/World_per_Capita_Consumption_of_Sugar.pdf (accessed 20.08.2022).</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">WHO sugar recommendations. Available at: https://www.ages.at/en/human/nutrition-food/nutrition-recommendations/who-sugarrecommendations (accessed 20.08.2022).</mixed-citation><mixed-citation xml:lang="en">WHO sugar recommendations. Available at: https://www.ages.at/en/human/nutrition-food/nutrition-recommendations/who-sugarrecommendations (accessed 20.08.2022).</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Ali A.M., Kunugi H. Approaches to nutritional screening in patients with coronavirus disease 2019 (COVID-19). Int J Environ Res Public Health. 2021; 18 (5): 2772. https://doi.org/10.3390/ijerph18052772.</mixed-citation><mixed-citation xml:lang="en">Ali A.M., Kunugi H. Approaches to nutritional screening in patients with coronavirus disease 2019 (COVID-19). Int J Environ Res Public Health. 2021; 18 (5): 2772. https://doi.org/10.3390/ijerph18052772.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Allard L., Ouedraogo E., Molleville J., et al. Malnutrition: percentage and association with prognosis in patients hospitalized for coronavirus disease 2019. Nutrients. 2020; 12 (12): 3679. https://doi.org/10.3390/nu12123679.</mixed-citation><mixed-citation xml:lang="en">Allard L., Ouedraogo E., Molleville J., et al. Malnutrition: percentage and association with prognosis in patients hospitalized for coronavirus disease 2019. Nutrients. 2020; 12 (12): 3679. https://doi.org/10.3390/nu12123679.</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Akhtar S., Das J.K., Ismail T., et al. Nutritional perspectives for the prevention and mitigation of COVID-19. Nutr Rev. 2021; 79 (3): 289– 300. https://doi.org/10.1093/nutrit/nuaa063.</mixed-citation><mixed-citation xml:lang="en">Akhtar S., Das J.K., Ismail T., et al. Nutritional perspectives for the prevention and mitigation of COVID-19. Nutr Rev. 2021; 79 (3): 289– 300. https://doi.org/10.1093/nutrit/nuaa063.</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Mentella M.C., Scaldaferri F., Gasbarrini A., Miggiano G.A.D. The role of nutrition in the COVID-19 pandemic. Nutrients. 2021; 13 (4): 1093. https://doi.org/10.3390/nu13041093.</mixed-citation><mixed-citation xml:lang="en">Mentella M.C., Scaldaferri F., Gasbarrini A., Miggiano G.A.D. The role of nutrition in the COVID-19 pandemic. Nutrients. 2021; 13 (4): 1093. https://doi.org/10.3390/nu13041093.</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">Morais A., Aquino J.S., da Silva-Maia J.K., et al. Nutritional status, diet and viral respiratory infections: perspectives for severe acute respiratory syndrome coronavirus 2. Br J Nutr. 2021; 125 (8): 851–62. https://doi.org/10.1017/S0007114520003311.</mixed-citation><mixed-citation xml:lang="en">Morais A., Aquino J.S., da Silva-Maia J.K., et al. Nutritional status, diet and viral respiratory infections: perspectives for severe acute respiratory syndrome coronavirus 2. Br J Nutr. 2021; 125 (8): 851–62. https://doi.org/10.1017/S0007114520003311.</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Sahin E., Orhan C., Uckun F.M., Sahin K. Clinical impact potential of supplemental nutrients as adjuncts of therapy in high-risk COVID-19 for obese patients. Front Nutr. 2020; 7: 580504. https://doi.org/10.3389/fnut.2020.580504.</mixed-citation><mixed-citation xml:lang="en">Sahin E., Orhan C., Uckun F.M., Sahin K. Clinical impact potential of supplemental nutrients as adjuncts of therapy in high-risk COVID-19 for obese patients. Front Nutr. 2020; 7: 580504. https://doi.org/10.3389/fnut.2020.580504.</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Clemente-Suárez V.J., Ramos-Campo D.J., Mielgo-Ayuso J., et al. Nutrition in the actual COVID-19 pandemic. A narrative review. Nutrients. 2021; 13 (6): 1924. https://doi.org/10.3390/nu13061924.</mixed-citation><mixed-citation xml:lang="en">Clemente-Suárez V.J., Ramos-Campo D.J., Mielgo-Ayuso J., et al. Nutrition in the actual COVID-19 pandemic. A narrative review. Nutrients. 2021; 13 (6): 1924. https://doi.org/10.3390/nu13061924.</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">James P.T., Ali Z., Armitage A.E., et al. The role of nutrition in COVID-19 susceptibility and severity of disease: a systematic review. J Nutr. 2021; 151 (7): 1854–78. https://doi.org/10.1093/jn/nxab059.</mixed-citation><mixed-citation xml:lang="en">James P.T., Ali Z., Armitage A.E., et al. The role of nutrition in COVID-19 susceptibility and severity of disease: a systematic review. J Nutr. 2021; 151 (7): 1854–78. https://doi.org/10.1093/jn/nxab059.</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Mortaz E., Bezemer G., Alipoor S.D., et al. Nutritional impact and its potential consequences on COVID-19 severity. Front Nutr. 2021; 8: 698617. https://doi.org/10.3389/fnut.2021.698617.</mixed-citation><mixed-citation xml:lang="en">Mortaz E., Bezemer G., Alipoor S.D., et al. Nutritional impact and its potential consequences on COVID-19 severity. Front Nutr. 2021; 8: 698617. https://doi.org/10.3389/fnut.2021.698617.</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Protein and amino acid requirements in human nutrition. World Health Organ Tech Rep Ser. 2007; 935: 1–265.</mixed-citation><mixed-citation xml:lang="en">Protein and amino acid requirements in human nutrition. World Health Organ Tech Rep Ser. 2007; 935: 1–265.</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Rothenberg E. Coronavirus disease 19 from the perspective of ageing with focus on nutritional status and nutrition management – a narrative review. Nutrients. 2021; 13 (4): 1294. https://doi.org/10.3390/nu13041294.</mixed-citation><mixed-citation xml:lang="en">Rothenberg E. Coronavirus disease 19 from the perspective of ageing with focus on nutritional status and nutrition management – a narrative review. Nutrients. 2021; 13 (4): 1294. https://doi.org/10.3390/nu13041294.</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Food and Agriculture Organization of the United Nations. Eating healthy before, during and after COVID-19. Available at: http://www.fao.org/fao-stories/article/en/c/1392499/ (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">Food and Agriculture Organization of the United Nations. Eating healthy before, during and after COVID-19. Available at: http://www.fao.org/fao-stories/article/en/c/1392499/ (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">Greene M.W., Roberts A.P., Frugé A.D. Negative association between Mediterranean diet adherence and COVID-19 cases and related deaths in Spain and 23 OECD countries: an ecological study. Front Nutr. 2021; 8: 591964. https://doi.org/10.3389/fnut.2021.591964.</mixed-citation><mixed-citation xml:lang="en">Greene M.W., Roberts A.P., Frugé A.D. Negative association between Mediterranean diet adherence and COVID-19 cases and related deaths in Spain and 23 OECD countries: an ecological study. Front Nutr. 2021; 8: 591964. https://doi.org/10.3389/fnut.2021.591964.</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Kim H., Rebholz C.M., Hegde S., et al. Plant-based diets, pescatarian diets and COVID-19 severity: a population-based case-control study in six countries. BMJ Nutr Prev Health. 2021; June 7. https://doi.org/10.1136/bmjnph-2021-000272.</mixed-citation><mixed-citation xml:lang="en">Kim H., Rebholz C.M., Hegde S., et al. Plant-based diets, pescatarian diets and COVID-19 severity: a population-based case-control study in six countries. BMJ Nutr Prev Health. 2021; June 7. https://doi.org/10.1136/bmjnph-2021-000272.</mixed-citation></citation-alternatives></ref><ref id="cit48"><label>48</label><citation-alternatives><mixed-citation xml:lang="ru">Food and Agriculture Organization of the United Nations. Food Balances (2010-). Available at: https://FAO.org/faostat/en/#data/FBS (accessed 20.07.2022).</mixed-citation><mixed-citation xml:lang="en">Food and Agriculture Organization of the United Nations. Food Balances (2010-). Available at: https://FAO.org/faostat/en/#data/FBS (accessed 20.07.2022).</mixed-citation></citation-alternatives></ref><ref id="cit49"><label>49</label><citation-alternatives><mixed-citation xml:lang="ru">Barberis E., Amede E., Tavecchia M., et al. Understanding protection from SARS-CoV-2 using metabolomics. Sci Rep. 2021; 11 (1): 13796. https://doi.org/10.1038/s41598-021-93260-2.</mixed-citation><mixed-citation xml:lang="en">Barberis E., Amede E., Tavecchia M., et al. Understanding protection from SARS-CoV-2 using metabolomics. Sci Rep. 2021; 11 (1): 13796. https://doi.org/10.1038/s41598-021-93260-2.</mixed-citation></citation-alternatives></ref><ref id="cit50"><label>50</label><citation-alternatives><mixed-citation xml:lang="ru">Schüler R., Osterhof M.A., Frahnow T., et al. High-saturated-fat diet increases circulating angiotensin-converting enzyme, which is enhanced by the rs4343 polymorphism defining persons at risk of nutrient-dependent increases of blood pressure. J Am Heart Assoc. 2017; 6 (1): e004465. https://doi.org/10.1161/JAHA.116.004465.</mixed-citation><mixed-citation xml:lang="en">Schüler R., Osterhof M.A., Frahnow T., et al. High-saturated-fat diet increases circulating angiotensin-converting enzyme, which is enhanced by the rs4343 polymorphism defining persons at risk of nutrient-dependent increases of blood pressure. J Am Heart Assoc. 2017; 6 (1): e004465. https://doi.org/10.1161/JAHA.116.004465.</mixed-citation></citation-alternatives></ref><ref id="cit51"><label>51</label><citation-alternatives><mixed-citation xml:lang="ru">Bousquet J., Anto J.M., Iaccarino G., et al. Is diet partly responsible for differences in COVID-19 death rates between and within countries? Clin Transl Allergy. 2020; 10: 16. https://doi.org/10.1186/s13601-020-00323-0.</mixed-citation><mixed-citation xml:lang="en">Bousquet J., Anto J.M., Iaccarino G., et al. Is diet partly responsible for differences in COVID-19 death rates between and within countries? Clin Transl Allergy. 2020; 10: 16. https://doi.org/10.1186/s13601-020-00323-0.</mixed-citation></citation-alternatives></ref><ref id="cit52"><label>52</label><citation-alternatives><mixed-citation xml:lang="ru">Paoli A., Gorini S., Caprio M. The dark side of the spoon – glucose, ketones and COVID-19: a possible role for ketogenic diet? J Transl Med. 2020; 18 (1): 441. https://doi.org/10.1186/s12967-020-02600-9.</mixed-citation><mixed-citation xml:lang="en">Paoli A., Gorini S., Caprio M. The dark side of the spoon – glucose, ketones and COVID-19: a possible role for ketogenic diet? J Transl Med. 2020; 18 (1): 441. https://doi.org/10.1186/s12967-020-02600-9.</mixed-citation></citation-alternatives></ref><ref id="cit53"><label>53</label><citation-alternatives><mixed-citation xml:lang="ru">Csapó J., Csilla A. Methods and procedures for reducing soy trypsin inhibitor activity by means of heat treatment combined with chemical methods. Acta Universitatis Sapientiae, Alimentaria. 2018; 11 (1): 58– 80. https://doi.org/10.2478/ausal-2018-0004.</mixed-citation><mixed-citation xml:lang="en">Csapó J., Csilla A. Methods and procedures for reducing soy trypsin inhibitor activity by means of heat treatment combined with chemical methods. Acta Universitatis Sapientiae, Alimentaria. 2018; 11 (1): 58– 80. https://doi.org/10.2478/ausal-2018-0004.</mixed-citation></citation-alternatives></ref><ref id="cit54"><label>54</label><citation-alternatives><mixed-citation xml:lang="ru">Losso J.N. The biochemical and functional food properties of the bowman-birk inhibitor. Crit Rev Food Sci Nutr. 2008; 48 (1): 94–118. https://doi.org/10.1080/10408390601177589.</mixed-citation><mixed-citation xml:lang="en">Losso J.N. The biochemical and functional food properties of the bowman-birk inhibitor. Crit Rev Food Sci Nutr. 2008; 48 (1): 94–118. https://doi.org/10.1080/10408390601177589.</mixed-citation></citation-alternatives></ref><ref id="cit55"><label>55</label><citation-alternatives><mixed-citation xml:lang="ru">Srikanth S., Chen Z. Plant protease inhibitors in therapeutics-focus on cancer therapy. Front Pharmacol. 2016; 7; 470. https://doi.org/10.3389/fphar.2016.00470.</mixed-citation><mixed-citation xml:lang="en">Srikanth S., Chen Z. Plant protease inhibitors in therapeutics-focus on cancer therapy. Front Pharmacol. 2016; 7; 470. https://doi.org/10.3389/fphar.2016.00470.</mixed-citation></citation-alternatives></ref><ref id="cit56"><label>56</label><citation-alternatives><mixed-citation xml:lang="ru">Billinger E., Zuo S., Johansson G. Characterization of serine protease inhibitor from Solanum tuberosum conjugated to soluble dextran and particle carriers. ACS Omega. 2019; 4 (19): 18456–64. https://doi.org/10.1021/acsomega.9b02815.</mixed-citation><mixed-citation xml:lang="en">Billinger E., Zuo S., Johansson G. Characterization of serine protease inhibitor from Solanum tuberosum conjugated to soluble dextran and particle carriers. ACS Omega. 2019; 4 (19): 18456–64. https://doi.org/10.1021/acsomega.9b02815.</mixed-citation></citation-alternatives></ref><ref id="cit57"><label>57</label><citation-alternatives><mixed-citation xml:lang="ru">Komarnytsky S., Cook A., Raskin I. Potato protease inhibitors inhibit food intake and increase circulating cholecystokinin levels by a trypsindependent mechanism. Int J Obes (Lond). 2011; 35 (2): 236–43. https://doi.org/10.1038/ijo.2010.192.</mixed-citation><mixed-citation xml:lang="en">Komarnytsky S., Cook A., Raskin I. Potato protease inhibitors inhibit food intake and increase circulating cholecystokinin levels by a trypsindependent mechanism. Int J Obes (Lond). 2011; 35 (2): 236–43. https://doi.org/10.1038/ijo.2010.192.</mixed-citation></citation-alternatives></ref><ref id="cit58"><label>58</label><citation-alternatives><mixed-citation xml:lang="ru">Ali S.G., Ansari M.A., Alzohairy M.A., et al. Natural products and nutrients against different viral diseases: prospects in prevention and treatment of SARS-CoV-2. Medicina (Kaunas). 2021; 57 (2): 169. https://doi.org/10.3390/medicina57020169.</mixed-citation><mixed-citation xml:lang="en">Ali S.G., Ansari M.A., Alzohairy M.A., et al. Natural products and nutrients against different viral diseases: prospects in prevention and treatment of SARS-CoV-2. Medicina (Kaunas). 2021; 57 (2): 169. https://doi.org/10.3390/medicina57020169.</mixed-citation></citation-alternatives></ref><ref id="cit59"><label>59</label><citation-alternatives><mixed-citation xml:lang="ru">Fuzimoto A.D., Isidoro C. The antiviral and coronavirus-host protein pathways inhibiting properties of herbs and natural compounds – additional weapons in the fight against the COVID-19 pandemic? J Tradit Complement Med. 2020; 10 (4): 405–19. https://doi.org/10.1016/j.jtcme.2020.05.003.</mixed-citation><mixed-citation xml:lang="en">Fuzimoto A.D., Isidoro C. The antiviral and coronavirus-host protein pathways inhibiting properties of herbs and natural compounds – additional weapons in the fight against the COVID-19 pandemic? J Tradit Complement Med. 2020; 10 (4): 405–19. https://doi.org/10.1016/j.jtcme.2020.05.003.</mixed-citation></citation-alternatives></ref><ref id="cit60"><label>60</label><citation-alternatives><mixed-citation xml:lang="ru">Li Z., Li X., Huang Y.Y., et al. Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs. Proc Natl Acad Sci. 2020; 3; 117 (44): 27381–7. https://doi.org/10.1073/pnas.2010470117.</mixed-citation><mixed-citation xml:lang="en">Li Z., Li X., Huang Y.Y., et al. Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs. Proc Natl Acad Sci. 2020; 3; 117 (44): 27381–7. https://doi.org/10.1073/pnas.2010470117.</mixed-citation></citation-alternatives></ref><ref id="cit61"><label>61</label><citation-alternatives><mixed-citation xml:lang="ru">Chitsike L., Duerksen-Hughes P. Keep out! SARS-CoV-2 entry inhibitors: their role and utility as COVID-19 therapeutics. Virol J. 2021; 18 (1): 154. https://doi.org/10.1186/s12985-021-01624-x.</mixed-citation><mixed-citation xml:lang="en">Chitsike L., Duerksen-Hughes P. Keep out! SARS-CoV-2 entry inhibitors: their role and utility as COVID-19 therapeutics. Virol J. 2021; 18 (1): 154. https://doi.org/10.1186/s12985-021-01624-x.</mixed-citation></citation-alternatives></ref><ref id="cit62"><label>62</label><citation-alternatives><mixed-citation xml:lang="ru">Guedes I.A., Costa L.S.C., dos Santos K.B., et al. Drug design and repurposing with DockThor-VS web server focusing on SARS-CoV-2 therapeutic targets and their non-synonym variants. Sci Rep. 2021; 11 (1): 5543. https://doi.org/10.1038/s41598-021-84700-0.</mixed-citation><mixed-citation xml:lang="en">Guedes I.A., Costa L.S.C., dos Santos K.B., et al. Drug design and repurposing with DockThor-VS web server focusing on SARS-CoV-2 therapeutic targets and their non-synonym variants. Sci Rep. 2021; 11 (1): 5543. https://doi.org/10.1038/s41598-021-84700-0.</mixed-citation></citation-alternatives></ref><ref id="cit63"><label>63</label><citation-alternatives><mixed-citation xml:lang="ru">Riva L., Yuan S., Yin X., et al. Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing. Nature. 2020; 586 (7827): 113–9. https://doi.org/10.1038/s41586-020-2577-1.</mixed-citation><mixed-citation xml:lang="en">Riva L., Yuan S., Yin X., et al. Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing. Nature. 2020; 586 (7827): 113–9. https://doi.org/10.1038/s41586-020-2577-1.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
