COVID-19 is not an Independent Cause of Death

The COVID-19 pandemic has had overwhelming global impacts with deleterious social, economic, and health consequences. To assess the COVID-19 death toll researchers have estimated declines in 2020 life expectancy at birth. Because data are often available only for COVID-19 deaths, the risks of dying from COVID-19 are assumed to be independent of those from other causes. We explore the soundness of this assumption based on data from the US and Brazil, the countries with the largest number of reported COVID-19 deaths. We use three methods. One estimates the difference between 2019 and 2020 life tables and therefore does not require the assumption of independence. The other two assume independence to simulate scenarios in which COVID-19 mortality is added to 2019 death rates or is eliminated from 2020 rates. Our results reveal that COVID-19 is not independent of other causes of death. The assumption of independence can lead to either an overestimate (Brazil) or an underestimate (US) of the decline in e0, depending on how the number of other reported causes of death changed in 2020.

Predicting SARS-CoV-2 variant spread in a completely seropositive population using semi-quantitative antibody measurements in blood donors

BackgroundSARS-CoV-2 serologic surveys estimate the proportion of the population with antibodies against historical variants which nears 100% in many settings. New analytic approaches are required to exploit the full information in serosurvey data. MethodUsing a SARS-CoV-2 anti-Spike (S) protein chemiluminescent microparticle assay, we attained a semi-quantitative measurement of population IgG titres in serial cross-sectional monthly samples of routine blood donations across seven Brazilian state capitals (March 2021-November 2021). In an ecological analysis (unit of analysis: age-city-calendar month) we assessed the relative contributions of prior attack rate and vaccination to antibody titre in blood donors. We compared blood donor anti-S titre across the seven cities during the growth phase of the Delta variant of concern (VOC) and use this to predict the resulting age-standardized incidence of severe COVID-19 cases. ResultsOn average we tested 780 samples per month in each location. Seroprevalence rose to >95% across all seven capitals by November 2021. Driven proximally by vaccination, mean antibody titre increased 16-fold over the study. The extent of prior natural infection shaped this process, with the greatest increases in antibody titres occurring in cities with the highest prior attack rates. Mean anti-S IgG was a strong predictor (adjusted R2 =0.89) of the number of severe cases caused by the Delta VOC in the seven cities. ConclusionsSemi-quantitative anti-S antibody titres are informative about prior exposure and vaccination coverage and can inform on the potential impact of future SARS-CoV-2 variants. SummaryIn the face of near 100% SARS-CoV-2 seroprevalence, we show that average semi-quantitative anti-S titre predicted the extent of the Delta variants spread in Brazil. This is a valuable metric for future seroprevalence studies.

Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gammas spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gammas detection, and were largely transient after Gammas detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazils COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazils COVID-19 deaths in hospitals could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries. NoteThe following manuscript has appeared as Report 46 - Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals at https://spiral.imperial.ac.uk:8443/handle/10044/1/91875. One sentence summaryCOVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity.

Estimating the early impact of immunization against COVID-19 on deaths among elderly people in Brazil: analyses of secondary data on vaccine coverage and mortality.

BackgroundVaccination against COVID-19 in Brazil started in January 2021, with health workers and the elderly as the priority groups. We assessed whether there was an impact of vaccinations on the mortality of elderly individuals in a context of wide transmission of the SARS-CoV-2 gamma (P.1) variant. MethodsBy May 27, 2021, 147238,414 COVID-19 deaths had been reported to the Brazilian Mortality Information System. Denominators for mortality rates were calculated by correcting population estimates for all-cause deaths reported in 2020. Proportionate mortality at ages 70-79 and 80+ years relative to deaths at all ages were calculated for deaths due to COVID-19 and to other causes, as were COVID-19 mortality rate ratios relative to individuals aged 0-69 years. Vaccine coverage data were obtained from the Ministry of Health. All results were tabulated by epidemiological weeks 1-19, 2021. FindingsThe proportion of all COVID-19 deaths at ages 80+ years was over 25% in weeks 1-6 and declined rapidly to 12.4% in week 19, whereas proportionate COVID-19 mortality for individuals aged 70-79 years started to decline by week 15. Trends in proportionate mortality due to other causes remained stable. Mortality rates were over 13 times higher in the 80+ years age group compared to that of 0-69 year olds up to week 6, and declined to 5.0 times in week 19. Vaccination coverage (first dose) of 90% was reached by week 9 for individuals aged 80+ years and by week 13 for those aged 70-79 years. Coronavac accounted for 65.4% and AstraZeneca for 29.8% of all doses administered in weeks 1-4, compared to 36.5% and 53.3% in weeks 15-19, respectively. InterpretationRapid scaling up of vaccination coverage among elderly Brazilians was associated with important declines in relative mortality compared to younger individuals, in a setting where the gamma variant predominates. Had mortality rates among the elderly remained proportionate to what was observed up to week 6, an estimated additional 43,802 COVID-related deaths would have been expected up to week 19.

Reduction in the 2020 Life Expectancy in Brazil after COVID-19

Brazil has the second-largest number of COVID-19 deaths worldwide. We use data on reported deaths to measure and compare the death toll across states from a demographic perspective. We estimate a decline in 2020 life expectancy at birth of 1.94 years, resulting in a mortality level not seen since 2013. The reduction in life expectancy at age 65 was 1.58 years, setting Brazil back to 2009 levels. The decline was larger for males, widening by 2.3% and 5.4% the female-male gap in life expectancy at birth and at age 65, respectively. Among states, Amazonas lost 59.6% of the improvements in life expectancy at birth since 2000. With 2021 COVID-19 deaths at about 43% of the total 2020 figures (as of mid-March) the demographic effect is likely to be even higher this year.

Role of Heterogeneous Transmission in the Decline of COVID-19 Cases During Winter of 2020/2021 in Massachusetts

ImportanceHeterogeneity in transmission of COVID-19 is a significant multiscale phenomenon. However, the role of this heterogeneity in shaping the overall dynamics of disease transmission is not well understood. ObjectiveTo investigate the role of heterogeneous transmission among different towns in Massachusetts in shaping the dynamics of COVID-19 transmission, especially the recent decline during winter of 2020/2021. Design, Setting, ParticipantsAnalysis of COVID-19 data collected and archived by the Massachusetts Department of Public Health. ExposuresThe entire population of the state of Massachusetts is exposed to the virus responsible for COVID-19, to varying degrees. This study quantifies this variation. Main outcome measuresWeekly observations, by town, on confirmed COVID-19 cases in Massachusetts, during the period (April 15th, 2020 to February 9th 2021). ResultsThe relative decline in COVID-19 cases, during January 12th, 2021 to February 9th, 2021, in the group of towns with higher total accumulated cases in the period before January 12th, 2021 is significantly larger than the corresponding relative decline in the group of towns with lower accumulated cases during the same period. Conclusions and RelevanceHeterogeneous nature of transmission is playing a significant role in shaping the rapid recent decline (January 12th to February 9th, 2021) in reported cases in Massachusetts, and probably around the country. These findings are relevant to how we estimate the threshold defining "herd" immunity, suggesting that we should account for effects due to heterogeneity. Key PointsO_ST_ABSQuestionC_ST_ABSDoes heterogeneity in disease transmission play a role in shaping the overall dynamics of COVID-19 in Massachusetts, including the recent decline in cases during the 2020/2021 winter. FindingsBased on analysis of data on cases in Massachusetts, the consistent and widespread decline of COVID-19 spread during winter of 2020/2021 (January 12th, 2021 to February 9th, 2021) appears to be shaped to a significant degree by the heterogeneous nature of transmission at the scale of different towns. Towns with a history of high (low) transmission rates during 2020 are experiencing a faster (slower) relative decline. MeaningWe suggest that heterogeneity in transmission of COVID-19 may impact the dynamics of disease transmission including the emergence of "herd" immunity, in line with some recent theoretical studies. This finding deserves some attention from other research groups investigating "herd" immunity, and from federal and state public health authorities concerned with the future evolution of the pandemic.

Temporal and geographical variation of COVID-19 in-hospital fatality rate in Brazil

BackgroundPrevious studies have shown that COVID-19 In-Hospital Fatality Rate (IHFR) varies between regions and has been diminishing over time. It is believed that the continuous improvement in the treatment of patients, age group of hospitalized, and the availability of hospital resources might be affecting the temporal and regional variation of IHFR. In this study, we explored how the IHFR varied over time and among age groups and federative states in Brazil. In addition, we also assessed the relationship between hospital structure availability and peaks of IHFR. MethodsA retrospective analysis of all COVID-19 hospitalizations with confirmed outcomes in 22 states between March 01 and September 22, 2020 (n=345,281) was done. We fit GLM binomial models with additive and interaction effects between age groups, epidemiological weeks, and states. We also evaluated the association between the modeled peak of IHFR in each state and the variables of hospital structure using the Spearman rank correlation test. ResultsWe found that the temporal variation of the IHFR was heterogeneous among the states, and in general it followed the temporal trends in hospitalizations. In addition, the peak of IHFR was higher in states with a smaller number of doctors and intensivists, and in states in which a higher percentage of people relied on the Public Health System (SUS) for medical care. ConclusionsOur results suggest that the pressure over the healthcare system is affecting the temporal trends of IHFR in Brazil. Key MessagesO_LITemporal variation of age adjusted In-Hospital Fatality Rate (IHFR) was markedly heterogeneous among Brazilian states from March to September of 2020. C_LIO_LIIn several states, the IHFR increased in association with the increase in the number of hospitalizations, which suggests that the overload of the healthcare system might be affecting the temporal trends of IHFR in Brazil. C_LIO_LIThe IHFR remained low in the states with higher rates of hospital resources, even with the high demand for hospitalization. C_LIO_LIThe number of doctors and intensivist physicians per habitant was more strongly correlated with the peak of IHFR in the Brazilian states than the number of ICU beds. C_LI

COVID-19 herd immunity in the Brazilian Amazon

The herd immunity threshold is the proportion of a population that must be immune to an infectious disease, either by natural infection or vaccination such that, in the absence of additional preventative measures, new cases decline and the effective reproduction number falls below unity. This fundamental epidemiological parameter is still unknown for the recently-emerged COVID-19, and mathematical models have predicted very divergent results. Population studies using antibody testing to infer total cumulative infections can provide empirical evidence of the level of population immunity in severely affected areas. Here we show that the transmission of SARS-CoV-2 in Manaus, located in the Brazilian Amazon, increased quickly during March and April and declined more slowly from May to September. In June, one month following the epidemic peak, 44% of the population was seropositive for SARS-CoV-2, equating to a cumulative incidence of 52%, after correcting for the false-negative rate of the antibody test. The seroprevalence fell in July and August due to antibody waning. After correcting for this, we estimate a final epidemic size of 66%. Although non-pharmaceutical interventions, plus a change in population behavior, may have helped to limit SARS-CoV-2 transmission in Manaus, the unusually high infection rate suggests that herd immunity played a significant role in determining the size of the epidemic.

Demand for hospitalization services for COVID-19 patients in Brazil

COVID-19 is now a pandemic and many of the affected countries face severe shortages of hospital resources. In Brazil, the first case was reported on February 26. As the number of cases grows in the country, there is a concern that the health system may become overwhelmed, resulting in shortages of hospital beds, intensive care unit beds, and mechanical ventilators. The timing of shortage is likely to vary geographically depending on the observed onset and pace of transmission observed, on the availability of resources, and on the actions implemented. Here we consider the daily number of cases reported in municipalities in Brazil to simulate twelve alternative scenarios of the likely timing of shortage, based on parameters consistently reported for China and Italy, on rates of hospital occupancy for other health conditions observed in Brazil in 2019, and on assumptions of allocation of patients in public and private facilities. Results show that hospital services could start to experience shortages of hospital beds, ICU beds, and ventilators in early April, the most critical situation observed for ICU beds. Increasing the allocation of beds for COVID-19 (in lieu of other conditions) or temporarily placing all resources under the administration of the state delays the anticipated start of shortages by a week. This suggests that solutions adopted by the Brazilian government must aim at expanding the available capacity (e.g., makeshift hospitals), and not simply prioritizing the allocation of available resources to COVID-19.