To evaluate the variations in COVID-19 case fatality rates (CFRs) across different regions and waves, and the impact of public health interventions, social and economic characteristics, and demographic factors on COVID-19 CFRs, we collected data from 30 countries with the highest incidence rate in three waves. We summarized the CFRs of different countries and continents in each wave through meta-analysis. Spearman’s correlation and multiple linear regression were employed to estimate the correlation between influencing factors and reduction rates of CFRs. Significant differences in CFRs were observed among different regions during the three waves (P < 0.001). An association was found between the changes in fully vaccinated rates (rs = 0.41), population density (rs = 0.43), the proportion of individuals over 65 years old (rs = 0.43), and the reduction rates of case fatality rate. Compared to Wave 1, the reduction rates in Wave 2 were associated with population density (β = 0.19, 95%CI: 0.05–0.33) and smoking rates (β = −4.66, 95%CI: −8.98 – −0.33), while in Wave 3 it was associated with booster vaccine rates (β = 0.60, 95%CI: 0.11–1.09) and hospital beds per thousand people (β = 4.15, 95%CI: 1.41–6.89). These findings suggest that the COVID-19 CFRs varied across different countries and waves, and promoting booster vaccinations, increasing hospital bed capacity, and implementing tobacco control measures can help reduce CFRs.

The COVID-19 epidemic showed inter-regional differences in Italy. We used an ecological study design and publicly available data to compare the basic reproduction number (R0), the doubling time of the infection (DT) and the COVID-19 cumulative incidence (CI), death rate, case fatality rate (CFR) and time lag to slow down up to a 50-days doubling time in the first and the second 2020 epidemic waves (δDT50) by region. We also explored socio-economic, environmental and lifestyle variables with multiple regression analysis. COVID-19 CI and CFR changed in opposite directions in the second vs. the first wave: the CI increased sixfold with no evidence of a relationship with the testing rate; the CFR decreased in the regions where it was initially higher but increased where it was lower. The R0 did not change; the initially mildly affected regions, but not those where the first wave had most severely hit, showed a greater δDT50 amplitude. Vehicular traffic, average temperature, population density, average income, education and household size showed a correlation with COVID-19 outcomes. The deadly experience in the first epidemic wave and the varying preparedness of the local health systems might have contributed to the inter-regional differences in the second COVID-19 epidemic wave.

The number of coronavirus disease 2019 (COVID-19) cases and deaths registered in Mexico during 2020 could be underestimated, due to the sentinel surveillance adopted in this country. Some consequences of following this type of epidemiological surveillance were the high case fatality rate and the high positivity rate for COVID-19 shown in Mexico in 2020. During this year, the Mexican Ministry of Health only considered cases from the public health system, which followed this sentinel surveillance, but did not consider those cases from the private health system. To better understand this pandemic, it is important to include all the results obtained by all the institutions capable of testing for COVID-19; thus, the Mexican Government could then make good decisions to protect the population from this disease.

Globally, severe acute malnutrition (SAM) accounts for >1/3–0⋅5 of deaths in children <5 years, and approximately 54 % deaths in developing countries. The minimum international standard set for the management of SAM is a cure rate of at least 75 % and death rate <10 %. The present study was conducted to determine treatment outcome and associated factors among children 1–5 years hospitalised with SAM in Lacor and Gulu Regional Referral Hospital (GRRH) in 2017. A retrospective observational method supplemented with a qualitative inquiry was done. A total of 317 patients’ records were reviewed in either hospital; checklist data were analysed using SPSS version 16 with P-values <0⋅05 considered for statistical significance. The case fatality rate (CFR) was 12⋅6 % (GRRH) and 9⋅5 % (Lacor). The average length of stay (LOS) was 14⋅69 d (GRRH) and 14⋅10 d (Lacor). There was statistical significance between Human Immunodeficiency Virus (HIV) status, blood transfusion, type of SAM, treatment provision at admission, antibiotics, mid-upper arm circumference (MUAC), hospital category and treatment outcome. In total, ten key informants were interviewed and they reported the presence of co-infections and severity of SAM complications as having an important bearing on treatment outcome. A significant proportion of patients were discharged not cured 19⋅9 % (Lacor) v. 16⋅4 % (GRRH). The CFR in GRRH was higher than the WHO recommendation. The LOS in both hospitals was within recommended. These results provide a generalisable problem in most African hospitals and could explain the persistently high rates of SAM in Africa.

In testimony before US Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was 10-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission.

Declining mortality following invasive pneumococcal disease (IPD) has been observed concurrent with a reduced incidence due to effective pneumococcal conjugate vaccines. However, with IPD now increasing due to serotype replacement, we undertook a statistical analysis to estimate the trend in all-cause 30-day case fatality rate (CFR) in the North East of England (NEE) following IPD. Clinical, microbiological and demographic data were obtained for all laboratory-confirmed IPD cases (April 2006–March 2016) and the adjusted association between CFR and epidemiological year estimated using logistic regression. Of the 2510 episodes of IPD included in the analysis, 486 died within 30 days of IPD (CFR 19%). Increasing age, male sex, a diagnosis of septicaemia, being in ⩾1 clinical risk groups, alcohol abuse and individual serotypes were independently associated with increased CFR. A significant decline in CFR over time was observed following adjustment for these significant predictors (adjusted odds ratio 0.93, 95% confidence interval 0.89–0.98; P = 0.003). A small but significant decline in 30-day all-cause CFR following IPD has been observed in the NEE. Nonetheless, certain population groups remain at increased risk of dying following IPD. Despite the introduction of effective vaccines, further strategies to reduce the ongoing burden of mortality from IPD are needed.