scholarly journals One hundred thirty-three observed COVID-19 deaths in 10 months: unpacking lower than predicted mortality in Rwanda

2021 ◽  
Vol 6 (2) ◽  
pp. e004547
Author(s):  
Clarisse Musanabaganwa ◽  
Vincent Cubaka ◽  
Etienne Mpabuka ◽  
Muhammed Semakula ◽  
Ernest Nahayo ◽  
...  
Keyword(s):  
Infection Control ◽  
Age Structure ◽  
Control Strategies ◽  
Age Distribution ◽  
Age Groups ◽  
Case Fatality ◽  
Population Level ◽  
African Region ◽  
Risk Of Death ◽  
First Case

The African region was predicted to have worse COVID-19 infection and death rates due to challenging health systems and social determinants of health. However, in the 10 months after its first case, Rwanda recorded 10316 cases and 133 COVID-19-related deaths translating to a case fatality rate (CFR) of 1.3%, which raised the question: why does Rwanda have a low COVID-19 CFR? Here we analysed COVID-19 data and explored possible explanations to better understand the disease burden in the context of Rwanda’s infection control strategies.We investigated whether the age distribution plays a role in the observed low CFR in Rwanda by comparing the expected number of deaths for 10-year age bands based on the CFR reported in other countries with the observed number of deaths for each age group. We found that the age-specific CFRs in Rwanda are similar to or, in some older age groups, slightly higher than those in other countries, suggesting that the lower population level CFR reflects the younger age structure in Rwanda, rather than a lower risk of death conditional on age. We also accounted for Rwanda’s comprehensive SARS-CoV-2 testing strategies and reliable documentation of COVID-19-related deaths and deduced that these measures may have allowed them to likely identify more asymptomatic or mild cases than other countries and reduced their reported CFR.Overall, the observed low COVID-19 deaths in Rwanda is likely influenced by the combination of effective infection control strategies, reliable identification of cases and reporting of deaths, and the population’s young age structure.

scholarly journals Estimating effective infection fatality rates during the course of the COVID-19 pandemic in Germany

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Christian Staerk ◽  
Tobias Wistuba ◽  
Andreas Mayr
Keyword(s):  
Age Distribution ◽  
Age Groups ◽  
Case Fatality ◽  
Time Dependent ◽  
Temporary Increase ◽  
International Studies ◽  
Age Group ◽  
Fatality Rate ◽  
Substantial Fraction ◽  
Second Wave

Abstract Background The infection fatality rate (IFR) of the Coronavirus Disease 2019 (COVID-19) is one of the most discussed figures in the context of this pandemic. In contrast to the case fatality rate (CFR), the IFR depends on the total number of infected individuals – not just on the number of confirmed cases. In order to estimate the IFR, several seroprevalence studies have been or are currently conducted. Methods Using German COVID-19 surveillance data and age-group specific IFR estimates from multiple international studies, this work investigates time-dependent variations in effective IFR over the course of the pandemic. Three different methods for estimating (effective) IFRs are presented: (a) population-averaged IFRs based on the assumption that the infection risk is independent of age and time, (b) effective IFRs based on the assumption that the age distribution of confirmed cases approximately reflects the age distribution of infected individuals, and (c) effective IFRs accounting for age- and time-dependent dark figures of infections. Results Effective IFRs in Germany are estimated to vary over time, as the age distributions of confirmed cases and estimated infections are changing during the course of the pandemic. In particular during the first and second waves of infections in spring and autumn/winter 2020, there has been a pronounced shift in the age distribution of confirmed cases towards older age groups, resulting in larger effective IFR estimates. The temporary increase in effective IFR during the first wave is estimated to be smaller but still remains when adjusting for age- and time-dependent dark figures. A comparison of effective IFRs with observed CFRs indicates that a substantial fraction of the time-dependent variability in observed mortality can be explained by changes in the age distribution of infections. Furthermore, a vanishing gap between effective IFRs and observed CFRs is apparent after the first infection wave, while an increasing gap can be observed during the second wave. Conclusions The development of estimated effective IFR and observed CFR reflects the changing age distribution of infections over the course of the COVID-19 pandemic in Germany. Further research is warranted to obtain timely age-stratified IFR estimates, particularly in light of new variants of the virus.

The age distribution in the Taimyr population wild northern deer (Rangifer Tarandus) in the first decades of 21 centuries

2021 ◽  
pp. 15-21
Author(s):  
A. Shapkin ◽  
R. Ivanova ◽  
N. Arsentseva ◽  
N. Sukhanova
Keyword(s):  
Age Structure ◽  
Rangifer Tarandus ◽  
Age Distribution ◽  
Age Groups ◽  
Base Material ◽  
Middle Level ◽  
Reproduction Rate ◽  
Male And Female ◽  
Field Samples ◽  
Wild Deer

Objective: mathematical demography means to identify and evaluate the age distribution of male and female of Taimyr tundra reindeer in the first decade of the XXI century and future trends in demographic situation Taimyr population.Materials and methods. The base material for evaluating the current state of the population age structure Taimyr steel fishing representative sample of male and female wild deer (n = 10845 individuals) collected in the West, Central and Taimyr Putorana in 2001-2008., And the deer samples (n = 1569 individuals), the floor of which is unknown. Determination of individual animals from age and older (n = 9773 individuals) performed on histological sections of cutters according to the corresponding procedure. To repay the random deviations of sample data because of a lack of presence of immature animals (calves, yearlings, young 1-2 years) (selectivity of fishing is directed primarily at the production of individuals older than 3 years, why animals in different age groups in the samples is greater than there are in the population) applies a smoothing procedure. Then, positive deviation of the number of individuals in the same age group were leveled due to negative deviations in adjacent groups.Results. By smoothed age ranges of the field samples from 2001-2008 the current age distribution of Taimyr wild reindeer calculated and analyzed. The study showed that the theoretical current age distribution of males with realized breeding is 77.03, females - 80.56, in the combined groups of animals - 82.35%. The real population has 18-19 age generations of males and females. The reproductive core of males from 3 to 10 years old is 48.43%, individuals of age limit 11 years and older occupy 1.96% of this sex and age structure, calves and young animals for 1-2 years - 24.64%. For the reproductive part of females aged 3–15 years, the overall age distribution is 55.34%, and the proportion of juveniles and young animals, according to calculations, is determined in this part of the population at 25.16%. In the combined current age distribution, males, females: calves and young animals accounted for 27.72%, the sexually mature part with animals of older and age-specific ages - 54.63%.Conclusion. Demographic Taimir population modeling operation in the first decade of the XXI century long materials commercial samples collected at commercial points shown at current age distribution of the realized and reproduction conditions for existing commercial load males - 77.03 for females - 80.56 and for unified groups (males, females) - 82.4%. Meanwhile, the steady state and stable age distribution Taimyr tundra wild deer can reach a middle-level only when the fecundity of female reproductive generations with clean reproduction rate (R0) equal in population groupings 1.0

Introduction to pertussis transmission and epidemiological dynamics

Pertussis ◽  
2018 ◽  
pp. 6-25
Author(s):  
Pejman Rohani ◽  
Samuel V. Scarpino
Keyword(s):  
Control Strategies ◽  
Age Distribution ◽  
Population Level ◽  
Vaccine Uptake ◽  
Effective Control ◽  
Transmission Potential ◽  
Epidemic Period ◽  
The Impact ◽  
Pertussis Epidemiology

Resolving the long-term, population-level consequences of changes in pertussis epidemiology, arising from bacterial evolution, shifts in vaccine-induced immunity, or changes in surveillance, are key challenges for devising effective control strategies. This chapter reviews some of the key features of pertussis epidemiology, together with the underlying epidemiological principles that set the context for their interpretation. These include the relationship between the age distribution of cases and pertussis transmission potential, the impact of vaccine uptake on incidence, periodicity and age incidence, as well as spatially explicit recurrent pertussis epidemics and associated extinction frequency. This review highlights some of the predictable and consistent aspects of pertussis epidemiology (e.g. the systematic increase in the inter-epidemic period with the introduction of whole-cell vaccines) and a number of important heterogeneities, including variations in contemporary patterns of incidence and geographic spread.

scholarly journals The demographic dividend is more than an education dividend

2020 ◽  
Vol 117 (42) ◽  
pp. 25982-25984
Author(s):  
Rainer Kotschy ◽  
Patricio Suarez Urtaza ◽  
Uwe Sunde
Keyword(s):  
Human Capital ◽  
Age Structure ◽  
Age Distribution ◽  
Age Groups ◽  
Demographic Dividend ◽  
Positive Growth ◽  
Working Age ◽  
Age Structured ◽  
Positive Effect ◽  
Effect Of Age

The demographic dividend has long been viewed as an important factor for economic development and provided a rationale for policies aiming at a more balanced age structure through birth control and family planning. Assessing the relative importance of age structure and increases in human capital, recent work has argued that the demographic dividend is related to education and has suggested a dominance of improving education over age structure. Here we reconsider the empirical relevance of shifts in the age distribution for development for a panel of 159 countries over the period 1950 to 2015. Based on a flexible model of age-structured human capital endowments, the results document important interactions between age structure and human capital endowments, suggesting that arguments of clear dominance of education over age structure are unwarranted and lead to potentially misleading policy conclusions. An increase in the working-age population share has a strong and significant positive effect on growth, even conditional on human capital, in line with the conventional notion of a demographic dividend. An increase in human capital only has positive growth effects if combined with a suitable age structure. An increasing share of the most productive age groups has an additional positive effect on economic performance. Finally, the results show considerable heterogeneity in the effect of age structure and human capital for different levels of development. Successful policies for sustainable development should take this heterogeneity into account to avoid detrimental implications of a unidimensional focus on human capital without accounting for demography.

scholarly journals Population age structure only partially explains the large number of COVID-19 deaths at the oldest ages

2020 ◽  
Author(s):  
Anthony Medford ◽  
Sergi Trias-Llimós
Keyword(s):  
Old Age ◽  
Age Structure ◽  
Age Distribution ◽  
Case Fatality ◽  
European Countries ◽  
Population Age Structure ◽  
Country Comparison ◽  
Cross Country ◽  
Age Structures

AbstractTo date any attention paid to the age shape of COVID-19 deaths has been mostly in relation to attempts to understand the differences in case fatality rates between countries. The aim of this paper is to explore differences in age distribution of deaths from COVID-19 among European countries which have old age structures. We do this by way of a cross-country comparison and put forward some reasons for potential differences.

scholarly journals The Characteristics, Dynamics, and the Risk of Death in COVID-19 Positive Dialysis Patients in London, UK

Kidney360 ◽  
2020 ◽  
Vol 1 (11) ◽  
pp. 1226-1243
Author(s):  
Dalvir Kular ◽  
Irina Chis Ster ◽  
Alexander Sarnowski ◽  
Eirini Lioudaki ◽  
Dandisonba C.B. Braide-Azikiwe ◽  
...  
Keyword(s):  
Risk Factors ◽  
Performance Status ◽  
Age Groups ◽  
Case Fatality ◽  
Smoking History ◽  
Case Fatality Ratio ◽  
Risk Of Death ◽  
Dialysis Vintage ◽  
Patients With Diabetes ◽  
Potential Risk Factors

BackgroundPatients on dialysis with frequent comorbidities, advanced age, and frailty, who visit treatment facilities frequently, are perhaps more prone to SARS-CoV-2 infection and related death—the risk factors and dynamics of which are unknown. The aim of this study was to investigate the hospital outcomes in patients on dialysis infected with SARS-CoV-2.MethodsData on 224 patients on hemodialysis between February 29, 2020 and May 15, 2020 with confirmed SARS-CoV-2 were analyzed for outcomes and potential risk factors for death, using a competing risk-regression model assessed by subdistribution hazards ratio (SHR).ResultsCrude data analyses suggest an overall case-fatality ratio of 23% (95% CI, 17% to 28%) overall, but that varies across age groups from 11% (95% CI, 0.9% to 9.2%) in patients ≤50 years old and 32% (95% CI, 17% to 48%) in patients >80 years; with 60% of deaths occurring in the first 15 days and 80% within 21 days, indicating a rapid deterioration toward death after admission. Almost 90% of surviving patients were discharged within 28 days. Death was more likely than hospital discharge in patients who were more frail (WHO performance status, 3–4; SHR, 2.16 [95% CI, 1.25 to 3.74]; P=0.006), had ischemic heart disease (SHR, 2.28 [95% CI, 1.32 to 3.94]; P=0.003), cerebrovascular disease (SHR, 2.11 [95% CI, 1.20 to 3.72]; P=0.01), smoking history (SHR, 2.69 [95% CI, 1.33 to 5.45]; P=0.006), patients who were hospitalized (SHR, 10.26 [95% CI, 3.10 to 33.94]; P<0.001), and patients with high CRP (SHR, 1.35 [95% CI, 1.10 to 1.67]) and a high neutrophil:lymphocyte ratio (SHR, 1.03 [95% CI, 1.01 to 1.04], P<0.001). Our data did not support differences in the risk of death associated with sex, ethnicity, dialysis vintage, or other comorbidities. However, comparison with the entire dialysis population attending these hospitals, in which 13% were affected, revealed that patients who were non-White (62% versus 52% in all patients, P=0.001) and those with diabetes (54% versus 22%, P<0.001) were disproportionately affected.ConclusionsThis report discusses the outcomes of a large cohort of patients on dialysis. We found SARS-CoV-2 infection affected more patients with diabetes and those who were non-White, with a high case-fatality ratio, which increased significantly with age, frailty, smoking, increasing CRP, and neutrophil:lymphocyte ratio at presentation.

scholarly journals Imported cases, community action, policy and institutional systems drive Hong Kong’s COVID-19 experience

2020 ◽  
Author(s):  
Christian Joy P. Cruz ◽  
Rachel Ganly ◽  
Zilin Li ◽  
Stuart Gietel-Basten
Keyword(s):  
Hong Kong ◽  
Age Structure ◽  
Age Distribution ◽  
Age Groups ◽  
Health Department ◽  
Community Action ◽  
Younger Age ◽  
Imported Cases ◽  
City State ◽  
The City

This paper investigates the profile of COVID-19 cases in Hong Kong, highlighting the unique age structure of confirmed cases compared to other states. Whilst the majority of cases in most states around the world have fitted an older age profile, our analysis shows that positive cases in Hong Kong have been concentrated amongst younger age groups, with the largest incidence of cases reported in the 15-24 age group. This is despite the population’s rapidly ageing structure and extremely high levels of population density. Using detailed case data from Hong Kong’s Centre for Health Department and Immigration Department, we analyze the sex and age distribution of the confirmed cases along with their recent travel histories and immigration flows for the period January to April, 2020. Our analysis highlights Hong Kong’s high proportion of imported cases and large overseas student population in developing COVID-19 hotspot areas such as the United Kingdom. Combined with targeted and aggressive early policy measures taken to contain the virus, these factors may have contributed to the uniquely younger age structure of COVID-19 cases in the city. Consequently, this young profile of confirmed cases may have prevented fatalities in the city-state.

scholarly journals Climate causes shifts in grey seal phenology by modifying age structure

2021 ◽  
Vol 288 (1964) ◽  
Author(s):  
James C. Bull ◽  
Owen R. Jones ◽  
Luca Börger ◽  
Novella Franconi ◽  
Roma Banga ◽  
...  
Keyword(s):  
Climate Change ◽  
Age Structure ◽  
Census Data ◽  
Age Distribution ◽  
Population Level ◽  
Ecosystem Change ◽  
Population Census ◽  
Sea Temperature ◽  
Population Age Structure ◽  
Phenological Shifts

There are numerous examples of phenological shifts that are recognized both as indicators of climate change and drivers of ecosystem change. A pressing challenge is to understand the causal mechanisms by which climate affects phenology. We combined annual population census data and individual longitudinal data (1992–2018) on grey seals, Halicheorus grypus , to quantify the relationship between pupping season phenology and sea surface temperature. A temperature increase of 2°C was associated with a pupping season advance of approximately seven days at the population level. However, we found that maternal age, rather than sea temperature, accounted for changes in pupping date by individuals. Warmer years were associated with an older average age of mothers, allowing us to explain phenological observations in terms of a changing population age structure. Finally, we developed a matrix population model to test whether our observations were consistent with changes to the stable age distribution. This could not fully account for observed phenological shift, strongly suggesting transient modification of population age structure, for example owing to immigration. We demonstrate a novel mechanism for phenological shifts under climate change in long-lived, age- or stage-structured species with broad implications for dynamics and resilience, as well as population management.

scholarly journals Covid-19 and Population Age Structure

2020 ◽  
Author(s):  
Ajit Haridas ◽  
Gangan Prathap
Keyword(s):  
Empirical Evidence ◽  
Age Structure ◽  
Age Distribution ◽  
Case Fatality ◽  
Mortality Rates ◽  
Epidemiological Studies ◽  
Cross Protection ◽  
Large Cohort ◽  
Population Age Structure

AbstractEpidemiological studies suggest that age distribution of a population has a non-trivial effect on how morbidity rates, mortality rates and case fatality rates (CFR) vary when there is an epidemic or pandemic. We look at the empirical evidence from a large cohort of countries to see the sensitivity of Covid-19 data to their respective median ages. The insights that emerge could be used to control for age structure effects while investigating other factors like cross-protection, comorbidities, etc.

scholarly journals Change in age distribution of COVID-19 deaths with the introduction of COVID-19 vaccination

2021 ◽  
Author(s):  
Roberta Pastorino ◽  
Angelo Maria Pezzullo ◽  
Leonardo Villani ◽  
Francesco Andrea Causio ◽  
Cathrine Axfors ◽  
...  
Keyword(s):  
Age Distribution ◽  
Age Groups ◽  
Prevalence Ratio ◽  
Population Level ◽  
Vaccination Programs ◽  
Vaccination Rates ◽  
Elderly Populations ◽  
The Difference ◽  
Age Independent ◽  
Vaccination Period

Background. Most countries initially deployed COVID-19 vaccines preferentially in elderly populations. Population-level vaccine effectiveness may be heralded by an increase in the proportion of deaths among non-elderly populations that were less covered by vaccination programs. Methods. We collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021-5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave). We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies. Findings. Countries that prioritized vaccination among older people saw an increasing share of deaths among 0-69 year old people in the vaccination versus the two control periods (summary prevalence ratio 1.32 [95 CI% 1.24-1.41] and 1.35 [95 CI% 1.26-1.44)]. No such change was seen on average in countries with age-independent vaccination policies (1.05 [95 CI% 0.78-1.41 and 0.97 [95 CI% 0.95- 1.00], respectively) and limited vaccination (0.93 [95 CI% 0.85-1.01] and 0.95 [95 CI% 0.87-1.03], respectively). Prevalence ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0-49 among all 0-69 deaths in the vaccination versus pre-vaccination periods. Interpretation. The substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly may herald the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths. Funding. This study received no specific funding.

Sign in / Sign up

Export Citation Format

Share Document