Characteristics of Population Reproduction in the Ural North

Numerous studies have been examining the influence of coronavirus on economic and demographic indicators of various countries and regions in the period from 2020 to 2021. However, little attention is paid to the consequences of the Covid-19 pandemic for Northern and Arctic regions. The present study aims to identify the characteristics of population reproduction in the northern oil and gas regions and consider factors affecting the morbidity and mortality from Covid-19 in the post-Soviet and coronavirus periods. In particular, Khanty-Mansi Autonomous Okrug - Yugra (KhMAO) and Yamalo-Nenets Autonomous Okrug (YaNAO), the Northern and Arctic regions of the Ural Federal District, were examined. The impact of the pandemic on population reproduction in the Ural North was assessed taking into account the regional demographic potential. To this end, the methods of retrospective and statistical analysis, aggregation, grouping, averaging and analogy approaches were utilised. The conducted retrospective analysis revealed the dependence of demographic processes on the time of settlement and development of the territory. In most regions and subregions of the Russian North and Arctic, with the exception of KhMAO and YaNAO, a gradual decrease in the population was observed. In 2020, mortality among patients with Covid-19 in the Ural North was lower than the national average, while the proportion of infected people to total population, on the contrary, was higher. This can be explained by the lower proportion of elderly in Yugra and YaNAO compared to other Russian regions. The research demonstrated that the mortality and birth rates in the most reproductive groups (people aged 20-29 and 30-39) were not affected by the Covid-19 pandemic. The main risk group is the older population aged 60-65 and over, determining the rate and number of deaths from coronavirus. The statistical analysis confirmed the existence of an eight-month cycle of Covid-19 waves from the lowest point to the peak. Future studies will focus on assessing the consequences of the pandemic for the population of the Arctic region at the municipal level.

Study of optimal vaccination strategies for early COVID-19 pandemic using an age-structured mathematical model: A case study of the USA.

In this paper we study different vaccination strategies that could have been implemented for the early COVID-19 pandemic. We use a demographic epidemiological mathematical model based on differential equations in order to investigate the efficacy of a variety of vaccination strategies under limited vaccine supply. We use the number of deaths as the metric to measure the efficacy of each of these strategies. Finding the optimal strategy for the vaccination programs is a complex problem due to the large number of variables that affect the outcomes. The constructed mathematical model takes into account demographic risk factors such as age, comorbidity status and social contacts of the population. We perform simulations to assess the performance of more than three million vaccination strategies which vary depending on the vaccine priority of each group. This study focuses on the scenario corresponding to the early vaccination period in the USA, but can be extended to other countries. The results of this study show the importance of designing an optimal vaccination strategy in order to save human lives. The problem is extremely complex due to the large amount of factors, high dimensionality and nonlinearities. We found that for low/moderate transmission rates the optimal strategy prioritizes high transmission groups, but for high transmission rates, the optimal strategy focuses on groups with high CFRs. The results provide valuable information for the design of optimal vaccination programs. Moreover, the results help to design scientific vaccination guidelines for future pandemics.

Awareness and Profiling of High-Risk Asbestos Exposure Groups in Australia

The increase in home improvement activity during the COVID-19 pandemic gave rise to concerns of increased asbestos exposure risk. This paper describes high-risk asbestos exposure groups based on current home improvement trends in Australia. A series of quantitative and qualitative studies were commissioned to better understand the attitudes, motivations, and behaviours of home improvers in Australia. In 2021, two in three Australian adults were inclined to undertake home improvement projects—big or small—with or without professional help, underscoring the importance of improving the asbestos safety knowledge and capacity of this cohort. The studies commissioned across 2020 and 2021 provide a deep analysis into this cohort, defining who they are and the segments that make up home improvers, their behaviours, and their asbestos awareness and attitudes. This knowledge enables the development and implementation of a range of targeted campaigns to increase asbestos awareness and prevent potential exposure to asbestos fibres. © 2023 by the authors.

Dynamics of household consumption after the COVID-19 pandemic in Ghana using input–output analysis

Purpose: This study analyzes the dynamic impact of the COVID-19 pandemic on consumption among Ghanaian households, by identifying the existing consumption inequalities in the households according to the different age categories of the household head and changes in consumption patterns among the household constituents. In particular, the study examines the effects of the coronavirus pandemic (COVID-19) on household consumption and the differing impact on the different age categories of the household. Design/methodology/approach: The research methodology of the study is based on the input–output analysis of the Ghanaian economy during the years 2015 and 2021 by using data on household consumption disaggregated by age. Economic impact is estimated through multi-sector modeling, specifically a demand model expressed based on a money metric measure valued in Ghanaian cedis. This model allows us to obtain the direct impact of the COVID-19 pandemic on the manufacturing sector, professional, scientific and technical activities, Water supply, sewerage, and waste management within Ghanaian households. The model also observed a negative impact of the COVID-19 pandemic on the public sector works and defense, and SSNIT sectors of the Ghanaian economy. Findings: The findings of the study revealed that for the category of age group between the ages of 15–29 years, the consumption of manufacturing products experienced an increase of 6.20% whiles that of electricity consumption, air conditioning and heating reduced by 2.26% for the period under consideration. However, public sector works and defense, and SSNIT experienced a decline by 8.24%. For the age group between 30 and 45 years, the highest and most positive percentage change in household consumption was noted to be professional, scientific and technical activities (6.20%), Water supply, sewerage, waste management (5.98%), as well as manufacturing (5.65%). However, there was a decline in the consumption level of education by Ghanaian households during the lockdown especially among people within the age group of 46–65 years. There was a decline of 6.11% for the administrative and support services and there was also a decline the services of defense and SSNIT service consumption by 2.10%. For the final age group of 66 years and above, there was an increase of 6.94% in the consumption of such essential utilities in Ghana between 2015 and 2021. The demand for education however showed a drastic reduction of 8.1% over the study period due to this category of age group with majority of them retiring from work. Research limitations/implications: The findings from this study will help in understanding the effects caused by the pandemic on household consumption and the differing impact on different age category of the household, especially on young households. This can potentially shape future policy by especially helping policymakers to device a more targeted social safety-net policies not only to speed-up recovery, but also to mitigate the negative impact of any future outbreak of a pandemic on household consumption and limit the age gaps in consumptions. However, the study does not consider the income levels of the different age groups. This becomes a limitation of the study and can be further explored in future studies. Originality/value: This study measures the impact of a global health pandemic on the consumption of all households, with its accompanying impact of this variation. It can be noted that analyzing household consumption and quantifying the positive and negative impact on different age category of the household and the different sectors of the Ghanaian economy add to the limited knowledge of the impact of the COVID-19 pandemic at the household level. © 2022, Emerald Publishing Limited.

Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality

The paper identifies major factors associated with the pandemic spread in the Russian regions, using econometric models and nonlinear «Random Forest» models to assess their significance. The study is based on data of the Russian regions for March-December 2020, a balanced panel sample included 780 observations. Prevalence of the pandemic was estimated based on the excess mortality rate. The study has identified a positive relationship between excess mortality and the share of migrants and a negative relationship between excess mortality and the share of pensioners in the region. Importance of climatic factors has been confirmed: high temperatures, other things being equal, reduce excess mortality, while high humidity, on the contrary, increases it. Excess mortality is higher in the regions with lower population mobility. Mortality is higher in the regions with high per capita incomes and regions with significant unemployment. Vice versa, excess mortality is lower in the regions with better doctor and nurse staffing levels. The study results show that in case of repeated waves of the epidemic or emergence of new viruses, public health policy should be geographically differentiated. Priority should be given to epidemiological situation in the regions with humid climate and low temperatures, high incomes, intensive migration, and high unemployment rates. Significant investments in medical education, higher number of medical specialists and their more even distribution across regions are required. This approach turns out to be more effective in terms of reducing mortality rather than restrictions on population mobility.

Age Structured Mathematical Modeling Studies on COVID-19 with respect to Combined Vaccination and Medical Treatment Strategies

In this study, we develop a mathematical model incorporating age-specific transmission dynamics of COVID-19 to evaluate the role of vaccination and treatment strategies in reducing the size of COVID-19 burden. Initially, we establish the positivity and boundedness of the solutions of the non controlled model and calculate the basic reproduction number and do the stability analysis. We then formulate an optimal control problem with vaccination and treatment as control variables and study the same. Pontryagin's Minimum Principle is used to obtain the optimal vaccination and treatment rates. Optimal vaccination and treatment policies are analysed for different values of the weight constant associated with the cost of vaccination and different efficacy levels of vaccine. Findings from these suggested that the combined strategies (vaccination and treatment) worked best in minimizing the infection and disease induced mortality. In order to reduce COVID-19 infection and COVID-19 induced deaths to maximum, it was observed that optimal control strategy should be prioritized to the population with age greater than 40 years. Varying the cost of vaccination it was found that sufficient implementation of vaccines (more than 77 %) reduces the size of COVID-19 infections and number of deaths. The infection curves varying the efficacies of the vaccines against infection were also analysed and it was found that higher efficacy of the vaccine resulted in lesser number of infections and COVID induced deaths. The findings would help policymakers to plan effective strategies to contain the size of the COVID-19 pandemic. © 2022 Bishal Chhetri et al., published by De Gruyter.

School and community reopening during the COVID-19 pandemic: a mathematical modelling study.

Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. Using demographic and epidemiological data between 31 July and 23 November 2020 from Toronto, Canada, we developed a compartmental transmission model with age, household and setting structure to study the impact of schools reopening in September 2020. The model simulates transmission in the home, community and schools, accounting for differences in infectiousness between adults and children, and accounting for work-from-home and virtual learning. While we found a slight increase in infections among adults (2.2%) and children (4.5%) within the first eight weeks of school reopening, transmission in schools was not the key driver of the virus resurgence in autumn 2020. Rather, it was community spread that determined the outbreak trajectory, primarily due to increases in contact rates among adults in the community after school reopening. Analyses of cross-infection among households, communities and schools revealed that home transmission is crucial for epidemic progression and safely operating schools, while the degree of in-person attendance has a larger impact than other control measures in schools. This study suggests that safe school reopening requires the strict maintenance of public health measures in the community.

An age-dependent immuno-epidemiological model with distributed recovery and death rates.

The work is devoted to a new immuno-epidemiological model with distributed recovery and death rates considered as functions of time after the infection onset. Disease transmission rate depends on the intra-subject viral load determined from the immunological submodel. The age-dependent model includes the viral load, recovery and death rates as functions of age considered as a continuous variable. Equations for susceptible, infected, recovered and dead compartments are expressed in terms of the number of newly infected cases. The analysis of the model includes the proof of the existence and uniqueness of solution. Furthermore, it is shown how the model can be reduced to age-dependent SIR or delay model under certain assumptions on recovery and death distributions. Basic reproduction number and final size of epidemic are determined for the reduced models. The model is validated with a COVID-19 case data. Modelling results show that proportion of young age groups can influence the epidemic progression since disease transmission rate for them is higher than for other age groups.

Characteristics of Population Reproduction in the Ural North

Numerous studies have been examining the influence of coronavirus on economic and demographic indicators of various countries and regions in the period from 2020 to 2021. However, little attention is paid to the consequences of the Covid-19 pandemic for Northern and Arctic regions. The present study aims to identify the characteristics of population reproduction in the northern oil and gas regions and consider factors affecting the morbidity and mortality from Covid-19 in the post-Soviet and coronavirus periods. In particular, Khanty-Mansi Autonomous Okrug - Yugra (KhMAO) and Yamalo-Nenets Autonomous Okrug (YaNAO), the Northern and Arctic regions of the Ural Federal District, were examined. The impact of the pandemic on population reproduction in the Ural North was assessed taking into account the regional demographic potential. To this end, the methods of retrospective and statistical analysis, aggregation, grouping, averaging and analogy approaches were utilised. The conducted retrospective analysis revealed the dependence of demographic processes on the time of settlement and development of the territory. In most regions and subregions of the Russian North and Arctic, with the exception of KhMAO and YaNAO, a gradual decrease in the population was observed. In 2020, mortality among patients with Covid-19 in the Ural North was lower than the national average, while the proportion of infected people to total population, on the contrary, was higher. This can be explained by the lower proportion of elderly in Yugra and YaNAO compared to other Russian regions. The research demonstrated that the mortality and birth rates in the most reproductive groups (people aged 20-29 and 30-39) were not affected by the Covid-19 pandemic. The main risk group is the older population aged 60-65 and over, determining the rate and number of deaths from coronavirus. The statistical analysis confirmed the existence of an eight-month cycle of Covid-19 waves from the lowest point to the peak. Future studies will focus on assessing the consequences of the pandemic for the population of the Arctic region at the municipal level. © 2022 Institute of Economics, Ural Branch of the Russian Academy of Sciences. All rights reserved.

POPULATION DEVELOPMENT IN CZECHIA IN 2021

The article analyses the demographic development of Czechia in 2021 and sets it in the context of demographic trends in the past decade and especially in the period 2016–2021. The study focuses on the main demographic processes, namely fertility, mortality, nuptiality, divorce rate, and migration. Population data in 2021 were adjusted to the 2021 Population Census. Demographic development was significantly influenced by the ongoing COVID-19 epidemic, the impact of which was most visible in the continued increase in mortality rates. The total fertility rate was the highest it has been in the last 30 years. The population of Czechia grew as a result of the positive balance of net migration, which was the highest in the last decade. © 2022, Demografie. All Rights Reserved.

Epidemic time series similarity is related to geographic distance and age structure.

Objective: More similar locations may have similar infectious disease dynamics. There is clear overlap in putative causes for epidemic similarity, such as geographic distance, age structure, and population size. We compare the effects of these potential drivers on epidemic similarity compared to a baseline assumption that differences in the basic reproductive number (R 0) will translate to differences in epidemic trajectories. Methods: Using COVID-19 case counts from United States counties, we explore the importance of geographic distance, population size differences, and age structure dissimilarity on resulting epidemic similarity. Results: We find clear effects of geographic space, age structure, population size, and R 0 on epidemic similarity, but notably the effect of age structure was stronger than the baseline assumption that differences in R 0 would be most related to epidemic similarity. Conclusions: Together, this highlights the role of spatial and demographic processes on SARS-CoV2 epidemics in the United States.

Characteristics of the Epidemic Situation Associated with Acute Respiratory Viral Infections in the Russian Federation during the Pandemic Spread of COVID-19

Annualy, SARS occupy a leading position in terms of morbidity and the magnitude of the economic damage caused both in the world and in the Russian Federation. Currently, the most widespread pandemics are caused by the influenza A (H1N1) pdm09 virus and the new SARS-CoV-2 coronavirus, which occupy a common ecological niche and require studying the manifestations of the epidemic process of ARVI for further development of measures to improve epidemiological surveillance of this group of infections. Aim of the study was to investigate the current manifestations of the epidemic process of ARVI and influenza, including in the context of a new coronavirus infection (COVID–19) pandemic, on the territory of Russia and in Moscow. Materials and methods. The assessment of the long-term dynamics of the incidence of ARVI and influenza (from 1999 to 2021), as well as its age structure in the territory of the Russian Federation and in Moscow, was carried out. The main sources of information were: WHO: «The situation with COVID-19 in the European region», the domestic information portal Stopkoronavirus.rf, as well as data from Federal State Statistical Observation forms No. 2 and No. 6. Results. During the period 2013–2019, a strong positive correlation was revealed between the incidence rates of ARVI in the Russian Federation and Moscow (p = 0.8, with p < 0.05), which became negative with the spread of SARS-CoV-2: in the country, the incidence rate of ARVI increased by 11.5% in 2020 and 15.6% in 2021., in Moscow there was a decrease of 45.1% than the average in Russia, which could be due to the quality of differential diagnosis of ARVI and COVID-19. In 2021 the incidence rate of influenza decreased by more than 2 times in all Federal Districts of the country, with the exception of the capital region, where it became the maximum-65.9 per 100 thousand population in 2021 (against 14.1 in 2019). In the age structure of influenza incidence, as well as ARVI, for the period from 2019 to 2021. the child population prevailed with the highest rates in the age groups of 1–2 years and 3–6 years. As the circulation of SARS-Cov-2 decreased to 15–19%, the activity of influenza viruses and other pathogens of the ARVI group increased (from 0.7–3.0% during the developed pandemic to 5.6–6.6% at the stage of its decline), which indicates a pronounced interference of pathogens detected at the global level in the system of Global Hospital Surveillance for flu. Conclusion. The forecast for the upcoming epidemic season 2022–2023 largely depends on the spread of the new coronavirus SARS-CoV-2, as well as its variability and the emergence of new variants. Nevertheless, there may be a significant increase in the incidence caused by the influenza A(H1N1)pdm09 virus, whose high activity was recorded in the current epidemic season in a number of countries in the Southern hemisphere. © 2022, Numikom. All rights reserved.

Comparing COVID-19 fatality across countries: a synthetic demographic indicator.

Background: The case fatality rate (CFR) is one of the most important measures for monitoring disease progression and evaluating appropriate policy health measures over the course of the COVID-19 pandemic. To remove biases arising from the age structure of COVID-19 cases in international comparisons of the CFR, existing studies have relied mainly on direct standardisation. Objective: We propose and validate a synthetic indicator of COVID-19 fatality (SCFR) that improves its comparability across countries by adjusting for the age and sex structure of COVID-19 cases without relying on the arbitrary choice of a standard population. Results: Contrary to what comparisons of the crude CFR suggest, differences in COVID-19 fatality across countries according to the proposed SCFR are not very stark. Importantly, once we adjust for the age structure of COVID-19 cases, the higher case fatality among men emerges as the main driver of international differences in COVID-19 CFR. Conclusions: The SCFR is a simple indicator that is useful for monitoring the fatality of SARS-CoV-2 mutations and the efficacy of health policy measures for COVID-19, including vaccination. Contributions: (1) A simple synthetic indicator of COVID-19 fatality that improves its comparability across countries by adjusting for the age and sex structure of COVID-19 cases; (2) Evidence that sex differences in COVID-19 fatality drive international differences in the overall CFR.

Assessing Age-Specific Vaccination Strategies and Post-vaccination Reopening Policies for COVID-19 Control Using SEIR Modeling Approach.

As the availability of COVID-19 vaccines, it is badly needed to develop vaccination guidelines to prioritize the vaccination delivery in order to effectively stop COVID-19 epidemic and minimize the loss. We evaluated the effect of age-specific vaccination strategies on the number of infections and deaths using an SEIR model, considering the age structure and social contact patterns for different age groups for each of different countries. In general, the vaccination priority should be given to those younger people who are active in social contacts to minimize the number of infections, while the vaccination priority should be given to the elderly to minimize the number of deaths. But this principle may not always apply when the interaction of age structure and age-specific social contact patterns is complicated. Partially reopening schools, workplaces or households, the vaccination priority may need to be adjusted accordingly. Prematurely reopening social contacts could initiate a new outbreak or even a new pandemic out of control if the vaccination rate and the detection rate are not high enough. Our result suggests that it requires at least nine months of vaccination (with a high vaccination rate > 0.1%) for Italy and India before fully reopening social contacts in order to avoid a new pandemic.

COVID-19 E SECURITIZAÇÃO DE SUAS AMEAÇAS NA ÁFRICA SUBSAARIANA

A rápida disseminação da nova doença do Coronavírus (COVID-19) é uma preocupação global significativa em termos de saúde e economia. Na África Subsaariana (ASS), há uma securitização emergente de suas ameaças percebidas devido às iniquidades socioeconômicas, sistemas de saúde inadequados e a prevalência de doenças na região. Em outras palavras, ela é apresentada ao público como uma ameaça existencial, com seus enquadramentos que projetam um quadro sombrio para a hospitalização, mortalidade, morbidade e resposta pandêmica da COVID-19 na ASS. Adotamos uma abordagem documental baseada em uma exploração crítica da teoria da securitização ao examinar as respostas da ASS à pandemia da COVID-19. Argumentamos que a securitização da COVID-19 na África é exagerada, com generalizações pessimistas que não consideram as condições e esforços locais dos governos e do Centro Africano de Controle de Doenças no gerenciamento da pandemia. Em vez de reestruturar demais as ameaças da COVID-19 na ASS, sugerimos que as realidades locais da região, estrutura etária, nível de urbanização, capacidades de auto-ajuda, contextos sócio-políticos e recursos disponíveis sejam considerados em qualquer estratégia de mitigação da pandemia.Alternate : The rapid spread of the novel Coronavirus disease (COVID-19) is a significant global health and economic concern. In sub-Saharan Africa (SSA), there is an emerging securitization of its perceived threats due to socio-economic inequities, inadequate healthcare systems, and the prevalence of diseases in the region. In other words, it is presented to the public as an existential threat with its attendant framings projecting a grim picture for COVID-19 hospitalization, mortality, morbidity, and pandemic response in SSA. We adopt a desk-based approach predicated on a critical exploration of securitization theory in examining SSA responses to the COVID-19 pandemic. We argue that COVID-19 securitization in Africa is exaggerated, with pessimistic generalizations that do not consider the local conditions and efforts by governments and the African Center for Disease Control in managing the pandemic. Rather than over-securitizing COVID-19 threats in SSA, we suggest that the region’s local realities, age structure, level of urbanization, self-help capabilities, socio-political contexts, and available resources be considered in any pandemic mitigation strategy.

Assessing Vaccination Prioritization Strategies for COVID-19 in South Africa Based on Age-Specific Compartment Model.

The vaccines are considered to be important for the prevention and control of coronavirus disease 2019 (COVID-19). However, considering the limited vaccine supply within an extended period of time in many countries where COVID-19 vaccine booster shot are taken and new vaccines are developed to suppress the mutation of virus, designing an effective vaccination strategy is extremely important to reduce the number of deaths and infections. Then, the simulations were implemented to study the relative reduction in morbidity and mortality of vaccine allocation strategies by using the proposed model and actual South Africa's epidemiological data. Our results indicated that in light of South Africa's demographics, vaccinating older age groups (>60 years) largely reduced the cumulative deaths and the "0-20 first" strategy was the most effective way to reduce confirmed cases. In addition, "21-30 first" and "31-40 first" strategies have also had a positive effect. Partial vaccination resulted in lower numbers of infections and deaths under different control measures compared with full vaccination in low-income countries. In addition, we analyzed the sensitivity of daily testing volume and infection rate, which are critical to optimize vaccine allocation. However, comprehensive reduction in infections was mainly affected by the vaccine proportion of the target age group. An increase in the proportion of vaccines given priority to "0-20" groups always had a favorable effect, and the prioritizing vaccine allocation among the "60+" age group with 60% of the total amount of vaccine consistently resulted in the greatest reduction in deaths. Meanwhile, we observed a significant distinction in the effect of COVID-19 vaccine allocation policies under varying priority strategies on relative reductions in the effective reproduction number. Our results could help evaluate to control measures performance and the improvement of vaccine allocation strategy for COVID-19 epidemic.

Mathematical modelling of vaccination rollout and NPIs lifting on COVID-19 transmission with VOC: a case study in Toronto, Canada.

BACKGROUND: Since December 2020, public health agencies have implemented a variety of vaccination strategies to curb the spread of SARS-CoV-2, along with pre-existing Nonpharmaceutical Interventions (NPIs). Initial strategies focused on vaccinating the elderly to prevent hospitalizations and deaths, but with vaccines becoming available to the broader population, it became important to determine the optimal strategy to enable the safe lifting of NPIs while avoiding virus resurgence. METHODS: We extended the classic deterministic SIR compartmental disease-transmission model to simulate the lifting of NPIs under different vaccine rollout scenarios. Using case and vaccination data from Toronto, Canada between December 28, 2020, and May 19, 2021, we estimated transmission throughout past stages of NPI escalation/relaxation to compare the impact of lifting NPIs on different dates on cases, hospitalizations, and deaths, given varying degrees of vaccine coverages by 20-year age groups, accounting for waning immunity. RESULTS: We found that, once coverage among the elderly is high enough (80% with at least one dose), the main age groups to target are 20-39 and 40-59 years, wherein first-dose coverage of at least 70% by mid-June 2021 is needed to minimize the possibility of resurgence if NPIs are to be lifted in the summer. While a resurgence was observed for every scenario of NPI lifting, we also found that under an optimistic vaccination coverage (70% coverage by mid-June, along with postponing reopening from August 2021 to September 2021) can reduce case counts and severe outcomes by roughly 57% by December 31, 2021. CONCLUSIONS: Our results suggest that focusing the vaccination strategy on the working-age population can curb the spread of SARS-CoV-2. However, even with high vaccination coverage in adults, increasing contacts and easing protective personal behaviours is not advisable since a resurgence is expected to occur, especially with an earlier reopening.

Delays, Masks, the Elderly, and Schools: First Covid-19 Wave in the Czech Republic.

Running across the globe for nearly 2 years, the Covid-19 pandemic keeps demonstrating its strength. Despite a lot of understanding, uncertainty regarding the efficiency of interventions still persists. We developed an age-structured epidemic model parameterized with epidemiological and sociological data for the first Covid-19 wave in the Czech Republic and found that (1) starting the spring 2020 lockdown 4 days earlier might prevent half of the confirmed cases by the end of lockdown period, (2) personal protective measures such as face masks appear more effective than just a realized reduction in social contacts, (3) the strategy of sheltering just the elderly is not at all effective, and (4) leaving schools open is a risky strategy. Despite vaccination programs, evidence-based choice and timing of non-pharmaceutical interventions remains an effective weapon against the Covid-19 pandemic.

Modeling waning and boosting of COVID-19 in Canada with vaccination.

SARS-CoV-2, the causative agent of COVID-19, has caused devastating health and economic impacts around the globe since its appearance in late 2019. The advent of effective vaccines leads to open questions on how best to vaccinate the population. To address such questions, we developed a model of COVID-19 infection by age that includes the waning and boosting of immunity against SARS-CoV-2 in the context of infection and vaccination. The model also accounts for changes to infectivity of the virus, such as public health mitigation protocols over time, increases in the transmissibility of variants of concern, changes in compliance to mask wearing and social distancing, and changes in testing rates. The model is employed to study public health mitigation and vaccination of the COVID-19 epidemic in Canada, including different vaccination programs (rollout by age), and delays between doses in a two-dose vaccine. We find that the decision to delay the second dose of vaccine is appropriate in the Canadian context. We also find that the benefits of a COVID-19 vaccination program in terms of reductions in infections is increased if vaccination of 15-19 year olds are included in the vaccine rollout.

A country-specific model of COVID-19 vaccination coverage needed for herd immunity in adult only or population wide vaccination programme.

We present a country specific method to calculate the COVID-19 vaccination coverage needed for herd immunity by considering age structure, age group-specific contact patterns, relative infectivity and susceptibility of children to adults, vaccination effectiveness and seroprevalence prior to vaccination. We find that across all six countries, vaccination of adults age 60 and above has little impact on Reff and this is could be due to the smaller number of contacts between this age group and the rest of the population according to the contact matrices used. If R0 is above 6, herd immunity by vaccine alone is unattainable for most countries either if vaccination is only available for adults or that vaccine effectiveness is lower at 65% against symptomatic infections. In this situation, additional control measures, booster shots, if they improve protection against infection, or the extension of vaccination to children, are required. For a highly transmissible variant with R0 up to 8, herd immunity is possible for all countries and for all four scenarios of varying relative infectivity and susceptibility of children compared to adults, if vaccine effectiveness is very high at 95% against symptomatic infections and that high vaccination coverage is achieved for both adults and children. In addition, we show that the effective reproduction number will vary between countries even if the same proportion of the population is vaccinated, depending on the demographics, the contact rates and the previous pre-vaccination seroprevalence in the country. This therefore means that care must be taken in extrapolating population level impacts of certain vaccine coverages from one country to another.