A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

Children aged 0-14 years had a far lower mortality risk during the entire COVID-19 pandemic in four major industrial countries: an observational study

The purpose of this study is to describe the morbidity and mortality of children during the entire COVID-19 pandemic. Age-disaggregated data of 108,003,741 cases and 560,426 deaths were collected from Canada, France, Germany, and Italy. The number of cases and deaths per million people per week, as well as case fatality rates (CFRs), were calculated for patients aged 0-14 and ≥ 15 years. During the first pandemic period in the four countries, starting from weeks 4 to 11 (in 2020) and ending at week 22 (in 2021), the number of deaths per million people per week and the CFRs in the ≥ 15 years age group were 500 to 2513 and 442 to 1662 times greater, respectively, than those in the 0-14 years age group. The number of deaths per million people per week was significantly lower in the first pandemic period than in the second pandemic period, which started at week 23 (2021) and ended from week 22 to week 25 (2023). During the second pandemic period in the four countries, the disparities between the ≥ 15 years and 0-14 years age groups decreased, and the number of deaths per million people per week in the ≥ 15 years age group was 76 to 180 times greater than it in the 0-14 years age group.

CONCLUSION

 Children aged 0-14 years had a far lower mortality risk during the entire COVID-19 pandemic, and the impact of viral variants and/or vaccination on the mortality rate is difficult to distinguish.

WHAT IS KNOWN

• Although extensive studies have focused on COVID-19-induced mortality, most of them are provisional reports performed during the unfolding of the pandemic and provide imprecise conclusion.

WHAT IS NEW

• We described the morbidity and mortality for children aged 0-14 years using complete survey data recorded during the entire COVID-19 pandemic. • The number of deaths per million people per week was far lower in children aged 0-14 years, while the number of deaths per million people per week in children aged 0-14 years was significantly higher in the second period which starting from week 23 (2021) and ending at week 22 to 25 (2023) than in the first period which starting from week 1 to 11 (2020) and ending at week 22 (2021).

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

BACKGROUND

The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19).

METHODOLOGY

PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542.

FINDINGS

In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias.

INTERPRETATION

The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

A quantitative evaluation of the impact of vaccine roll-out rate and coverage on reducing deaths: insights from the first 2 years of COVID-19 epidemic in Iran

BACKGROUND

Vaccination has played a pivotal role in reducing the burden of COVID-19. Despite numerous studies highlighting its benefits in reducing the risk of severe disease and death, we still lack a quantitative understanding of how varying vaccination roll-out rates influence COVID-19 mortality.

METHODS

We developed a framework for estimating the number of avertable COVID-19 deaths (ACDs) by vaccination in Iran. To achieve this, we compared Iran's vaccination roll-out rates with those of eight model countries that predominantly used inactivated virus vaccines. We calculated net differences in the number of fully vaccinated individuals under counterfactual scenarios where Iran's per-capita roll-out rate was replaced with that of the model countries. This, in turn, enabled us to determine age specific ACDs for the Iranian population under counterfactual scenarios where number of COVID-19 deaths are estimated using all-cause mortality data. These estimates covered the period from the start of 2020 to 20 April 2022.

RESULTS

We found that while Iran would have had an approximately similar number of fully vaccinated individuals under counterfactual roll-out rates based on Bangladesh, Nepal, Sri Lanka, and Turkey (~ 65-70%), adopting Turkey's roll-out rates could have averted 50,000 (95% confidence interval: 38,100-53,500) additional deaths, while following Bangladesh's rates may have resulted in 52,800 (17,400-189,500) more fatalities in Iran. Surprisingly, mimicking Argentina's slower roll-out led to only 12,600 (10,400-13,300) fewer deaths, despite a higher counterfactual percentage of fully vaccinated individuals (~ 79%). Emulating Montenegro or Bolivia, with faster per capita roll-out rates and approximately 50% counterfactual full vaccination, could have prevented more deaths in older age groups, especially during the early waves. Finally, replicating Bahrain's model as an upper-bound benchmark, Iran could have averted 75,300 (56,000-83,000) deaths, primarily in the > 50 age groups.

CONCLUSIONS

Our analysis revealed that faster roll-outs were consistently associated with higher numbers of averted deaths, even in scenarios with lower overall coverage. This study offers valuable insights into future decision-making regarding infectious disease epidemic management through vaccination strategies. It accomplishes this by comparing various countries' relative performance in terms of timing, pace, and vaccination coverage, ultimately contributing to the prevention of COVID-19-related deaths.

The Casualties of War: An Excess Mortality Estimate of Lives Lost in the 2020 Nagorno-Karabakh Conflict

Who and how many died in the 2020 Karabakh War? With limited evidence provided by authorities, media outlets, and human rights organizations, still little is known about the death toll caused by the 44-day conflict in and around Nagorno-Karabakh. This paper provides a first assessment of the human cost of the war. Using age-sex vital registration data from Armenia, Azerbaijan, and the de facto Republic of Artsakh/Nagorno-Karabakh, we difference the 2020 observed mortality values from expected deaths based on trends in mortality between 2015 and 2019 to offer sensible estimates of excess mortality resulting from the conflict. We compare and contrast our findings with neighboring peaceful countries with similar mortality patterns and socio-cultural background and discuss them against the backdrop of the concurrent first wave of Covid-19. We estimate that the war led to almost 6,500 excess deaths among people aged 15-49. Nearly 2,800 excess losses occurred in Armenia, 3,400 in Azerbaijan, and 310 in de facto Artsakh. Deaths were highly concentrated among late adolescent and young adult males, suggesting that most excess mortality was directly related to combat. Beyond the human tragedy, for small countries like Armenia and Azerbaijan, such loss of young men represents a considerable long-term cost for future demographic, economic, and social development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11113-023-09790-2.

The evolution of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.