How many more? Under-reporting of the COVID-19 deaths in Brazil in 2020

Americans' willingness to give to global immunization programs: Political heterogeneity in preferences for program management and response to priming communications

To develop effective private donation campaigns that support vaccine distribution in low- and middle-income countries (LMICs), one must understand donors' willingness to give, response to stimuli, and preferences for program management. We use a contingent valuation method to estimate United States citizens' willingness to give to nongovernmental COVID-19 immunization programs in LMICs during the emergency phase of the pandemic. Using split-sample treatments, we evaluate the impact of the immunization program administrator (generic NGO or COVAX) and the role of priming communications on inequality in income and vaccination rates between the US and recipient countries. Results show that the median American would donate $42 towards global immunization programs. Preferences for program management and responses to priming communications are heterogeneous across political affiliations, after controlling for altruistic motives, experiences with COVID, giving behaviors, and sociodemographic characteristics. Specifically, Democrats and Independents are more likely to donate to the COVAX-administered fund, and more responsive to priming statements regarding vaccine-gaps. Policy implications are discussed.

Using machine learning to estimate health spillover effects

We develop a nonparametric model to study health spillover effects of policy interventions. We use double/debiased machine learning to estimate the model using data from 74 hospitals in Rio de Janeiro, Brazil, and examine cross-patient spillover effects during the COVID-19 pandemic. The pandemic forced hospitals to develop new protocols to offer intensive care to both COVID and non-COVID patients. Our results show that the need to care for COVID patients affects health outcomes of non-COVID patients. Controlling for a number of confounders, we find that mortality rates and length of stay of non-COVID ICU patients increase when hospitals simultaneously offer intensive care to both types of patients. Policy simulations suggest that an increase in the number of ICU beds can counter morbidity spillover, but it is unlikely to be a feasible approach to counter mortality spillover.

Avoidable COVID-19-related deaths and hospitalizations in Brazil, 2020-2023

OBJECTIVE

To estimate the number of avoidable COVID-19 deaths and hospitalizations in Brazil.

METHODS

Secondary data on COVID-19 deaths and hospitalizations were related to two measures of cumulative vaccine coverage (in the last six months and before this period) by negative binomial regression to estimate population-level protective effectiveness (PLPE) against severe disease. The latter includes the overall protective effect of all COVID-19-preventive measures, such as direct and indirect vaccine effectiveness, social distancing, and lockdown, but only the vaccine coverage data were available for the regression analysis.

RESULTS

COVID-19 mortality rates per 100,000 inhabitants were 10.26, 16.45, 0.14, and 0.94, for the years 2020, 2021, 2022, and the first half of 2023. In the same order and scale, COVID-19 hospitalization rates were 28.96, 47.04, 0.40, and 3.74. Both hospitalizations and deaths peaked early in 2021, then sharply reduced by the end of the year as the first-dose vaccine coverage reached 90 %, and rose with the vaccine coverage within the last six months falling below 10 % in 2023. PLPE for preventing COVID-19 deaths was 19.9 %, 98.9 %, and 93.1 % for the years 2021, 2022, and the first half of 2023. Had Brazil vaccinated the same number of people against COVID-19 in the last quarter of 2020 as it did in the first quarter of 2021, over 117,000 deaths and 277,000 hospitalizations could have been avoided over the period analyzed.

CONCLUSIONS

PLPE reduction in 2023 was likely caused by low vaccine uptake. The disease burden could have been much lower had the vaccination started earlier and had the vaccine uptake not dropped so sharply in 2023.

Demographic and Geographic Characterization of Excess Mortality During the COVID-19 Pandemic in Baltimore City, Maryland, March 2020 to March 2021

Estimates of excess mortality can provide insight into direct and indirect impacts of the coronavirus disease 2019 (COVID-19) pandemic beyond deaths specifically attributed to COVID-19. We analyzed death certificate data from Baltimore City, Maryland, from March 1, 2020, to March 31, 2021, and found that 1,725 individuals (95% confidence interval: 1,495, 1,954) died in excess of what was expected from all-cause mortality trends in 2016-2019; 1,050 (61%) excess deaths were attributed to COVID-19. Observed mortality was 23%-32% higher than expected among individuals aged 50 years and older. Non-White residents of Baltimore City also experienced 2 to 3 times higher rates of excess mortality than White residents (e.g., 37.4 vs. 10.7 excess deaths per 10,000 population among Black residents vs. White residents). There was little to no observed excess mortality among residents of hospice, long-term care, and nursing home facilities, despite accounting for nearly 30% (312/1,050) of recorded COVID-19 deaths. There was significant geographic variation in excess mortality within the city, largely following racial population distributions. These results demonstrate the substantial and unequal impact of the COVID-19 pandemic on Baltimore City residents and the importance of building robust, timely surveillance systems to track disparities and inform targeted strategies to remediate the impact of future epidemics.

Characterizing deaths among adult patients with severe acute respiratory infection: during the pre- and COVID-19 pandemic periods in Bangladesh, 2018-2022

BACKGROUND

Severe acute respiratory infection (SARI) is a leading cause of mortality globally, peaking during the COVID-19 pandemic. We analyzed SARI-associated deaths during the pre-and-pandemic periods in Bangladesh to identify the contributing factors.

METHODS

We analyzed data from hospital-based influenza surveillance at nine tertiary-level hospitals in Bangladesh. We considered March 2018-February 2020 as the pre-pandemic period and March 2020-February 2022 as the pandemic period and included adult (≥ 18 years) participants in our study. Surveillance physicians identified WHO-SARI case definition meeting inpatients and collected demographics, clinical characteristics, and outcomes at hospital discharge and 30 days post-discharge. We performed rRT-PCR for influenza and SARS-CoV-2 viruses on collected nasopharyngeal and oropharyngeal swabs. We used multivariable Cox's regression models to calculate the hazard ratio (HR) for factors associated with SARI deaths in these adult patients.

RESULTS

We enrolled 4392 SARI patients during the pre-pandemic and 3824 SARI patients during the pandemic period. Case fatality ratio was higher during the pandemic: 13.62% (521) [in-hospital: 6.45% (247); post-discharge: 7.17% (274)] compared to pre-pandemic, 6.01% (264) [in-hospital: 2.01% (89), post-discharge: 4% (175)] (p < 0.001). Pre-pandemic, influenza was detected in 14% (37/264) of SARI deaths. Influenza was detected during the pandemic in 2.3% (12/521), SARS-CoV-2 in 41.8% (218/521), and both viruses in only one SARI death. History of smoking and the presence of 1 or more co-morbid conditions independently attributed to SARI deaths in adults in the pre-pandemic period. SARI deaths in such patients were also associated with respiratory difficulties on admission in both pre-pandemic (aHR 2.36; 95% CI:1.65-3.36) and pandemic period (aHR 2.30; 95% CI: 1.57-3.35) after accounting for age, sex, smoking status, presence of 1 or more co-morbid conditions, and detection of influenza and SARS-CoV-2 viruses.

CONCLUSIONS

During the pandemic, SARI mortality increased; influenza-associated mortality declined, and SARS-CoV-2 caused over a third of SARI deaths. Post-discharge mortality was higher than in-hospital mortality during both periods. Limiting premature discharge and strengthening post-discharge monitoring and nursing services could reduce unexpected deaths. Formative research to better understand post-discharge mortality is essential to reduce SARI deaths.

COVID-19 in Brazil: a 3-year update

Three years into the coronavirus disease (COVID)-19 pandemic and the world is still struggling with the aftermath of this global health crisis. In Brazil, we are witnessing serious economic, health, social, and political problems. The rapid spread of the virus in our country was the result of a shortage of vaccines and the lack of an effective national campaign to identify and report cases. This health crisis also intensified social inequalities, hitting Indigenous peoples hard due to the lack of access to health services. In addition, rising unemployment and overcrowding of the health system made contagion possible, especially among the most vulnerable, increasing the number of serious cases of the disease. It is important to highlight that emotional problems worsened, the educational system was severely affected, and domestic violence increased during the confinement period, in addition to the fact that the pandemic exposed the great disparities of regional inequalities that exist across the country, mainly concerning health management.

Gender differences in estimated excess mortality during the COVID-19 pandemic in Thailand

BACKGROUND

There is a limited body of research specifically examining gender inequality in excess mortality and its variations across age groups and geographical locations during the COVID-19 pandemic. This study aims to fill this gap by analyzing the patterns of gender inequality in excess all-cause mortality in Thailand during the COVID-19 pandemic.

METHODS

Data pertaining to all-cause deaths and population between January 1, 2010, and December 31, 2021, were obtained from Thailand's Bureau of Registration Administration. A seasonal autoregressive integrated moving average (SARIMA) technique was used to estimate excess mortality during the pandemic between January 2020 to December 2021. Gender differential excess mortality was measured as the difference in age-standardized mortality rates between men and women.

RESULTS

Our SARIMA-based estimate of all-cause mortality in Thailand during the COVID-19 pandemic amounted to 1,032,921 deaths, with COVID-19-related fatalities surpassing official figures by 1.64 times. The analysis revealed fluctuating patterns of excess and deficit in all-cause mortality rates across different phases of the pandemic, as well as among various age groups and regions. In 2020, the most pronounced gender disparity in excess all-cause mortality emerged in April, with 4.28 additional female deaths per 100,000, whereas in 2021, the peak gender gap transpired in August, with 7.52 more male deaths per 100,000. Individuals in the 80 + age group exhibited the largest gender gap for most of the observed period. Gender differences in excess mortality were uniform across regions and over the period observed. Bangkok showed the highest gender disparity during the peak of the fourth wave, with 24.18 more male deaths per 100,000.

CONCLUSION

The findings indicate an overall presence of gender inequality in excess mortality during the COVID-19 pandemic in Thailand, observed across age groups and regions. These findings highlight the need for further attention to be paid to gender disparities in mortality and call for targeted interventions to address these disparities.

Unmasking the COVID-19 pandemic prevention gains: excess mortality reversal in 2022

OBJECTIVES

The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions.

STUDY DESIGN

Excess mortality interrupted time series.

METHODS

Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths above the baseline during the pandemic (week 11 in 2020 to week 15 in 2022) (when public health interventions were in place) and during the post-pandemic period (week 16 in 2022 to week 52 in 2022) were calculated. These results were fitted to the linear regression model to determine any potential relationship between mortality during these two periods.

RESULTS

The model used in this study had high predictive value (adjusted R2 = 59.4%). Mortality during the endemic (post-pandemic) period alone increased by 7.2% (95% confidence interval [CI]: 5.7, 8.6) above baseline, while each percentage increase in mortality during the pandemic corresponded to a 0.357% reduction (95% CI: 0.243, 0.471) in mortality during the post-pandemic period.

CONCLUSIONS

The most successful countries in terms of protective measures also experienced the highest mortality rates after restrictions were lifted. The model used in this study clearly shows a measure of bidirectional mortality displacement that is sufficiently clear to mask any impact of long COVID on overall mortality. Results from this study also seriously impact previous cost-benefit analyses of pandemic prevention measures, since, according to the current model, 12.2% (95% CI: 8.3, 16.1) of the gains achieved in pandemic containment were lost after restrictions were lifted.

Long-term monitoring of COVID-19 prevalence in raw and treated wastewater in Salvador, the largest capital of the Brazilian Northeast

Wastewater-based epidemiology (WBE) becomes an interesting epidemiological approach to monitoring the prevalence of SARS-CoV-2 broadly and non-invasively. Herein, we employ for the first time WBE, associated or not with the PEG 8000 precipitation method, for the detection of SARS-CoV-2 in samples of raw or treated wastewater from 22 municipal wastewater treatment stations (WWTPs) located in Salvador, the fourth most populous city in Brazil. Our results demonstrate the success of the application of WBE for detecting SARS-CoV-2 in both types of evaluated samples, regardless of the usage of PEG 8000 concentration procedure. Further, an increase in SARS-CoV-2 positivity rate was observed in samples collected in months that presented the highest number of confirmed COVID-19 cases (May/2021, June/2021 and January/2022). While PEG 8000 concentration step was found to significantly increase the positivity rate in treated wastewater samples (p < 0.005), a strong positive correlation (r: 0.84; p < 0.002) between non-concentrated raw wastewater samples with the number of new cases of COVID-19 (April/2021-February/2022) was observed. In general, the present results reinforce the efficiency of WBE approach to monitoring the presence of SARS-CoV-2 in either low- or high-capacity WWTPs. The successful usage of WBE even in raw wastewater samples makes it an interesting low-cost tool for epidemiological surveillance.

Evaluation of concordance in estimation of excess mortality due to COVID-19 pandemic

BACKGROUND

The World Health Organization (WHO) kept track of COVID-19 data at country level daily during the pandemic that included the number of tests, infected cases and fatalities. This daily record was susceptible to change depending on the time and place and impacted by underreporting. In addition to reporting cases of excess COVID-19-related deaths, the WHO also provided estimates of excess mortality based on mathematical models.

OBJECTIVE

To evaluate the WHO reported and model-based estimate of excess deaths to determine the degree of agreement and universality.

METHODOLOGY

Epidemiological data gathered from nine different countries between April 2020 and December 2021 are used in this study. These countries are India, Indonesia, Italy, Russia, United Kingdom, Mexico, the United States, Brazil and Peru and each of them recorded more than 1.5 million deaths from COVID-19 during these months. Statistical tools including correlation, linear regression, intraclass correlation and Bland-Altman plots are used to assess the degree of agreement between reported and model-based estimates of excess deaths.

RESULTS

The WHO-derived mathematical model for estimating excess deaths due to COVID-19 was found to be appropriate for only four of the nine chosen countries, namely Italy, United Kingdom, the United States and Brazil. The other countries showed proportional biases and significantly high regression coefficients.

CONCLUSION

The study revealed that, for some of the chosen nations, the mathematical model proposed by the WHO is practical and capable of estimating the number of excess deaths brought on by COVID-19. However, the derived approach cannot be applied globally.

The relationship between staying at home during the pandemic and the number of conceptions: A national panel data analysis

hether the COVID-19 pandemic has changed fertility patterns is still an open question, as social isolation for long periods can impact the number of conceptions in many ways. We combine administrative data on all recent births in Brazil with daily data on individual location to estimate the relationship between the share of individuals staying close to their homes in each week and the number of conceptions in that same week, comparing municipalities with different social isolation patterns during the first semester of 2020. We find that conceptions unequivocally decline when social isolation increases. The effect is stronger for women who are between 21 and 25 years old and more educated, as well as for richer, larger, and more urban municipalities. COVID-19 is likely to change fertility across countries depending on the behavior of the population and on the lock-down measures implemented to fight the pandemic.

Impact of the early months of the COVID-19 pandemic on the sleep patterns of a Brazilian population sample

Humanitarian and health crisis have drastic effects on the physical and mental well-being of people. The COVID-19 pandemic forced many countries to impose containment measures on its population to halt the spread of the new coronavirus (SARS-CoV-2). This aim of this study was to explore self-reported sleep quality and insomnia symptoms in a sample of the Brazilian population before and during the COVID-19 quarantine period. Our data was collected through online questionnaires, including the Pittsburgh Sleep Quality Index, the Insomnia Severity Index, and the Sleep Hygiene Index. The final sample comprised 1,109 volunteers. Generalized estimating equations (GEE) revealed that during the initial months of the COVID-19 pandemic, alterations in self-reported sleep parameters were observed in the participants. Sleep efficiency and sleep duration increased, but there was a worsening in sleep quality and an increase in symptoms related to insomnia.

Assessing COVID-19 pandemic excess deaths in Brazil: Years 2020 and 2021

We estimated the impact of the COVID-19 pandemic on mortality in Brazil for 2020 and 2021 years. We used mortality data (2015-2021) from the Brazilian Health Ministry for forecasting baseline deaths under non-pandemic conditions and to estimate all-cause excess deaths at the country level and stratified by sex, age, ethnicity and region of residence, from March 2020 to December 2021. We also considered the estimation of excess deaths due to specific causes. The estimated all-cause excess deaths were 187 842 (95% PI: 164 122; 211 562, P-Score = 16.1%) for weeks 10-53, 2020, and 441 048 (95% PI: 411 740; 470 356, P-Score = 31.9%) for weeks 1-52, 2021. P-Score values ranged from 1.4% (RS, South) to 38.1% (AM, North) in 2020 and from 21.2% (AL and BA, Northeast) to 66.1% (RO, North) in 2021. Differences among men (18.4%) and women (13.4%) appeared in 2020 only, and the P-Score values were about 30% for both sexes in 2021. Except for youngsters (< 20 years old), all adult age groups were badly hit, especially those from 40 to 79 years old. In 2020, the Indigenous, Black and East Asian descendants had the highest P-Score (26.2 to 28.6%). In 2021, Black (34.7%) and East Asian descendants (42.5%) suffered the greatest impact. The pandemic impact had enormous regional heterogeneity and substantial differences according to socio-demographic factors, mainly during the first wave, showing that some population strata benefited from the social distancing measures when they could adhere to them. In the second wave, the burden was very high for all but extremely high for some, highlighting that our society must tackle the health inequalities experienced by groups of different socio-demographic statuses.

Discrepancies Between Preliminary and Final COVID-19 Mortality Data - the Case of Serbia

Since the start of the COVID-19 pandemic, countries have scrambled to set up data collection and dissemination pipelines. These data end up in various online datasets. While it has been evident from the beginning that these preliminary data produced by some countries are not very reliable, the mortality data from Serbia seemed particularly problematic. These data are included in all major COVID-19 databases and utilized for research purposes worldwide. Discrepancies were identified between the preliminary mortality data reported through the emergency necessitated system and the final mortality data generated by the regular vital statistics pipeline. The number of deaths due to COVID-19 in Serbia, as reported preliminarily, does not align with the final death toll, which is more than three times higher. To evaluate the impact of the problematic data on research, we identified databases that include these data and reviewed the articles that utilized them. Our literature review identified at least 86 studies that were impacted by these problematic data. We strongly advise researchers to disregard the preliminary COVID-19 mortality data from Serbia. If all-cause mortality data is available, any preliminary data should be validated using excess mortality.

Clinical and epidemiological aspects of severe acute respiratory infection: before and during the first year of the COVID-19 pandemic in Brazil

BACKGROUND

Widespread respiratory infections with high morbidity rates caused by respiratory viruses represent a significant global public health problem. Our objective was to describe cases and deaths from severe acute respiratory infection (SARI) in Brazil over the past 8 y as well as changes in the distribution and risk of illness and death from SARI before and in the first year of the coronavirus disease 2019 (COVID-19) pandemic (FYP).

METHODS

We performed a descriptive epidemiological study of hospitalized SARI cases and deaths between 2013 and 2020 in Brazil, separated into pre-pandemic (2013 to 2019) and FYP (2020). We estimate the increase in SARI cases and deaths in the FYP as well as the mortality and infection risks attributable to the FYP (MRAP and IRAP, respectively).

RESULTS

In 2020, an excess of 425 054 cases and 109 682 deaths was observed, with a significant increase in the risk of falling ill and dying from SARI, with an IRAP of 200.06 and an MRAP of 51.68 cases per 100 000 inhabitants. The increase in SARI cases and deaths was particularly prominent among patients with COVID-19, the elderly, males, those self-identifying as mixed race and patients with heart disease and diabetes. We conclude that an important increase in morbidity and mortality due to SARI was observed in the FYP. More vulnerable groups and those living in the Southeast, North and Center-West regions of the country suffered the most.

[Methodological proposal for evaluation of death records from COVID-19]

The limitation of studies on the coverage and completeness of death records is one of the main problems regarding vital statistics in Brazil. In 2020, the number of information systems on death records in Brazil increased due to the COVID-19 pandemic, generating more uncertainties about the quality of death records. This study proposed an evaluation of the quality of death records due to COVID-19. Three methodological stages were considered: estimation of deaths under-registration; redistribution of deaths from nonspecific causes (Garbage Codes), and redistribution of deaths from ill-defined causes to COVID-19 data. The proposal was applied in the State of Paraíba, Brazil, and its municipalities in 2020, by using the official records of the Brazilian Mortality Information System of the Brazilian Ministry of Health. In total, 1,281 deaths were retrieved, besides the 3,426 deaths officially recorded for Paraíba State, an increase of 37.4% in deaths from COVID-19. The proposal was effective, easy to apply, and can be used by managers of governmental spheres and people interested in it as a tool to assess the quality of death records for any geographic space, thus, contributing to a better understanding of the real effect of the pandemic.

COVID-19-related excess mortality - an overview of the current evidence

Analysis of excess deaths, defined as the difference in the total number of deaths in an emergency compared to the number of deaths expected under normal conditions, allows a more reliable assessment of the impact on health systems caused by the global threat of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2). So far, data for the two years of the pandemic (2020-2021) indicates the occurrence of 14.9 million excess deaths according to WHO (World Health Organization) estimates. The purpose of the analysis conducted was to define the concept and identify the causes of excess mortality during the COVID-19 pandemic. Inconsistent and unreliable death registration systems; overburdened health systems in low- and middle-income countries; reduced access to medical services for patients with health problems other than COVID-19; the introduction of social distancing and lockdown rules, which translated into increased deaths from psychiatric illnesses and addictions; political considerations and media messages that interfered with vaccination acceptance and adherence; and the additional impact of other natural disasters (hurricanes, floods, drought) were identified as the most important reasons for excess deaths occurrence. The correct identification of country-specific factors and the correct response and countermeasures taken appear crucial in terms of limiting the negative impact of the current pandemic, but also of future threats of a similar nature, in order to reduce excess deaths.

Ethnic/Racial Disparity in Mortality from COVID-19: Data for the Year 2020 in Brazil

The study aimed to investigate ethnic/racial disparities in COVID-19 mortality in Brazilian federative units and their respective capitals in 2020. Population data and number of COVID-19 deaths were extracted by skin color (white, black, brown and indigenous) from all Brazilian states and their respective capitals. The mortality rate of COVID-19 by ethnicity in Brazilian states was higher between people from brown skin color, followed by indigenous and black. Only in one state, in the Federal District and in the federal capital, age-standardized mortality rates were higher among white's people. There is a high percentage of deaths from COVID-19 higher than expected among non-white individuals, especially in south-central states and capitals of the country. Mortality from COVID-19 affect ethnic-racial groups unevenly in Brazil and the number of excess deaths among non-whites was over 9000. Urgent government measures are needed to reduce the racial disparity in health indicators in Brazil.

Evaluation of SARS-CoV-2 concentrations in wastewater and river water samples

There are only a few established methods to determine the concentration of encapsulated viruses, such as SARS-CoV-2, in water matrices, limiting the application of wastewater-based epidemiology (WBE)—an important tool for public health research. The present study compared four methods that are commonly used to concentrate non-encapsulated enteric viruses for determining SARS-CoV-2 concentration in wastewater and wastewater-enriched river water samples. The four methods tested were electronegative membrane with Mg⁺² addition, aluminum hydroxide-based precipitation, polyethylene glycol (PEG) 8000 precipitation, and ultrafiltration (with porosity of 10 and 50 kDa). Prior to the concentration step, filtration or centrifugation was performed to remove suspended particles from the samples (pretreatment). To evaluate the recovery efficiency (%), samples of SARS-CoV-2 from nasopharyngeal swabs obtained from RT-qPCR-positive patients were used as spiked samples. The second part of the analysis involved the quantification of the SARS-CoV-2 copy number in analytes without SARS-CoV-2-spiked samples. Among the tested methods, pretreatment via centrifugation followed by ultrafiltration with a 50-kDa cut-off was found the most efficient method for wastewater samples with spiked samples (54.3 or 113.01% efficiency). For the wastewater-enriched river samples with spiked samples, pretreatment via centrifugation followed by filtration using an electronegative membrane was the most efficient method (110.8% and 95.9% for N1 and N2 markers, respectively). However, ultrafiltration of the raw river water samples using 10 or 50 kDa cut-off filters and PEG 8000 precipitation showed the best concentration efficiency based on copy number, regardless of the pretreatment approach or sample type (values ranging from 3 × 10⁵ to 6.7 × 10³). The effectiveness of the concentration method can vary depending on the type of sample and concentration method. We consider that this study will contribute to more widespread use of WBE for the environmental surveillance of SARS-CoV-2.

Spatiotemporal Bayesian estimation of the number of under-reported COVID-19 cases in Victoria Australia

Having an estimate of the number of under-reported cases is crucial in determining the true burden of a disease. In the COVID-19 pandemic, there is a great need to quantify the true disease burden by capturing the true incidence rate to establish appropriate measures and strategies to combat the disease. This study investigates the under-reporting of COVID-19 cases in Victoria, Australia, during the third wave of the pandemic as a result of variation in geographic area and time. It is aimed to determine potential under-reported areas and generate the true picture of the disease in terms of the number of cases. A two-tiered Bayesian hierarchical model approach is employed to estimate the true incidence and detection rates through Bayesian model averaging. The proposed model goes beyond testing inequality across areas by looking into other covariates such as weather, vaccination rates, and access to vaccination and testing centres, including interactions and variations between space and time. This model aims for parsimony yet allows a broader range of scope to capture the underlying dynamic of the reported COVID-19 cases. Moreover, it is a data-driven, flexible, and generalisable model to a global context such as cross-country estimation and across time points under strict pandemic conditions.

Wastewater-based epidemiology: A Brazilian SARS-COV-2 surveillance experience

Since 2020, developed countries have rapidly shared both publicly and academically relevant wastewater surveillance information. Data on SARS-CoV-2 circulation is pivotal for guiding public health policies and improving the COVID-19 pandemic response. Conversely, low- and middle-income countries, such as Latin America and the Caribbean, showed timid activities in the Wastewater-Based Epidemiology (WBE) context. In these countries, isolated groups perform viral wastewater monitoring, and the data are unevenly shared or accessible to health agencies and the scientific community. This manuscript aims to highlight the relevance of a multiparty effort involving research, public health, and governmental agencies to support usage of WBE methodology to its full potential during the COVID-19 pandemic as part of a joint One Health surveillance approach. Thus, in this study, we explored the results obtained from wastewater surveillance in different regions of Brazil as a part of the COVID-19 Wastewater Monitoring Network ANA (National Water Agency), MCTI (Ministry of Science, Technology, and Innovations) and MS (Ministry of Health). Over the epidemiological weeks of 2021 and early 2022, viral RNA concentrations in wastewater followed epidemiological trends and variations. The highest viral loads in wastewater samples were detected during the second Brazilian wave of COVID-19. Corroborating international reports, our experience demonstrated usefulness of the WBE approach in viral surveillance. Wastewater surveillance allows hotspot identification, and therefore, early public health interventions. In addition, this methodology allows tracking of asymptomatic and oligosymptomatic individuals, who are generally underreported, especially in emerging countries with limited clinical testing capacity. Therefore, WBE undoubtedly contributes to improving public health responses in the context of this pandemic, as well as other sanitary emergencies.

da Paixão Melo M, Ferreira da Silva M, de Jesus Gonçalves dos Santos N, de Souza Pessoa N, Silva de Araujo R, de Macedo Godim T, Fraga de Oliveira Tosta S, Brandão Nardy V, Cristina Faria E, Frederico de Carvalho Dominguez Souza B, Laís Almeida dos Santos J, Wikramaratna P, Giovanetti M, Alcântara LCJ, Lourenço J, Leal e Silva de Mello A. Dynamics and Determinants of SARS-CoV-2 RT-PCR Testing on Symptomatic Individuals Attending Healthcare Centers during 2020 in Bahia, Brazil

RT-PCR testing data provides opportunities to explore regional and individual determinants of test positivity and surveillance infrastructure. Using Generalized Additive Models, we explored 222,515 tests of a random sample of individuals with COVID-19 compatible symptoms in the Brazilian state of Bahia during 2020. We found that age and male gender were the most significant determinants of test positivity. There was evidence of an unequal impact among socio-demographic strata, with higher positivity among those living in areas with low education levels during the first epidemic wave, followed by those living in areas with higher education levels in the second wave. Our estimated probability of testing positive after symptom onset corroborates previous reports that the probability decreases with time, more than halving by about two weeks and converging to zero by three weeks. Test positivity rates generally followed state-level reported cases, and while a single laboratory performed ~90% of tests covering ~99% of the state's area, test turn-around time generally remained below four days. This testing effort is a testimony to the Bahian surveillance capacity during public health emergencies, as previously witnessed during the recent Zika and Yellow Fever outbreaks.

Communication, information, and knowledge in the pandemic by COVID-19 in Brazil

As coronavirus disease 2019 (COVID-19) is asserting itself as a health crisis, it is necessary to assess the knowledge and perceptions of people about the disease. The aim of this study is to assess the knowledge of the general population about COVID-19 and how the media influence this knowledge. This is a cross-sectional study with 5066 participants who answered an online questionnaire between April and May 2020. Data analysis was performed using descriptive statistics and logistic regression models. Over 75% have obtained a high degree of knowledge regarding signs, symptoms, and transmission, 95% stated to check the veracity of the information received, and also showed that the total knowledge about COVID-19 was associated with the level of instruction, with the perception of the quality of information disseminated by the media, and with the risk perception. Despite the high level of knowledge of participants, the results pointed to the need to reinforce information for individuals with less education and the importance of avoiding denialism that reduces the risk perception about COVID-19.

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

Background

The COVID-19 is a significant public health issue, and monitoring confirmed cases and deaths is an essential epidemiologic tool. We evaluated the features in Brazilian hospitalized patients due to severe acute respiratory infection (SARI) during the COVID-19 pandemic in Brazil. We grouped the patients into the following categories: Influenza virus infection (G1), other respiratory viruses' infection (G2), other known etiologic agents (G3), SARS-CoV-2 infection (patients with COVID-19, G4), and undefined etiological agent (G5).

Methods

We performed an epidemiological study using data from DataSUS (https://opendatasus.saude.gov.br/) from December 2019 to October 2021. The dataset included Brazilian hospitalized patients due to SARI. We considered the clinical evolution of the patients with SARI during the COVID-19 pandemic according to the SARI patient groups as the outcome. We performed the multivariate statistical analysis using logistic regression, and we adopted an Alpha error of 0.05.

Results

A total of 2,740,272 patients were hospitalized due to SARI in Brazil, being the São Paulo state responsible for most of the cases [802,367 (29.3%)]. Most of the patients were male (1,495,416; 54.6%), aged between 25 and 60 years (1,269,398; 46.3%), and were White (1,105,123; 49.8%). A total of 1,577,279 (68.3%) patients recovered from SARI, whereas 701,607 (30.4%) died due to SARI, and 30,551 (1.3%) did not have their deaths related to SARI. A major part of the patients was grouped in G4 (1,817,098; 66.3%) and G5 (896,207; 32.7%). The other groups account for &lt;1% of our sample [G1: 3,474 (0.1%), G2: 16,627 (0.6%), and G3: 6,866 (0.3%)]. The deaths related to SARI were more frequent in G4 (574,887; 34.7%); however, the deaths not related to SARI were more frequent among the patients categorized into the G3 (1,339; 21.3%) and G5 (25,829; 4.1%). In the multivariate analysis, the main predictors to classify the patients in the G5 when compared with G4 or G1-G4 were female sex, younger age, Black race, low educational level, rural place of residence, and the use of antiviral to treat the clinical signs. Furthermore, several features predict the risk of death by SARI, such as older age, race (Black, Indigenous, and multiracial background), low educational level, residence in a flu outbreak region, need for intensive care unit, and need for mechanical ventilatory support.

Conclusions

The possible COVID-19 underreporting (G5) might be associated with an enhanced mortality rate, more evident in distinct social groups. In addition, the patients' features are unequal between the patients' groups and can be used to determine the risk of possible COVID-19 underreporting in our population. Patients with a higher risk of death had a different epidemiological profile when compared with patients who recovered from SARI, like older age, Black, Indigenous, and multiracial background races, low educational level, residence in a flu outbreak region, need for intensive care unit and need for mechanical ventilatory support.

Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21

BACKGROUND

Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021.

METHODS

All-cause mortality reports were collected for 74 countries and territories and 266 subnational locations (including 31 locations in low-income and middle-income countries) that had reported either weekly or monthly deaths from all causes during the pandemic in 2020 and 2021, and for up to 11 year previously. In addition, we obtained excess mortality data for 12 states in India. Excess mortality over time was calculated as observed mortality, after excluding data from periods affected by late registration and anomalies such as heat waves, minus expected mortality. Six models were used to estimate expected mortality; final estimates of expected mortality were based on an ensemble of these models. Ensemble weights were based on root mean squared errors derived from an out-of-sample predictive validity test. As mortality records are incomplete worldwide, we built a statistical model that predicted the excess mortality rate for locations and periods where all-cause mortality data were not available. We used least absolute shrinkage and selection operator (LASSO) regression as a variable selection mechanism and selected 15 covariates, including both covariates pertaining to the COVID-19 pandemic, such as seroprevalence, and to background population health metrics, such as the Healthcare Access and Quality Index, with direction of effects on excess mortality concordant with a meta-analysis by the US Centers for Disease Control and Prevention. With the selected best model, we ran a prediction process using 100 draws for each covariate and 100 draws of estimated coefficients and residuals, estimated from the regressions run at the draw level using draw-level input data on both excess mortality and covariates. Mean values and 95% uncertainty intervals were then generated at national, regional, and global levels. Out-of-sample predictive validity testing was done on the basis of our final model specification.

FINDINGS

Although reported COVID-19 deaths between Jan 1, 2020, and Dec 31, 2021, totalled 5·94 million worldwide, we estimate that 18·2 million (95% uncertainty interval 17·1-19·6) people died worldwide because of the COVID-19 pandemic (as measured by excess mortality) over that period. The global all-age rate of excess mortality due to the COVID-19 pandemic was 120·3 deaths (113·1-129·3) per 100 000 of the population, and excess mortality rate exceeded 300 deaths per 100 000 of the population in 21 countries. The number of excess deaths due to COVID-19 was largest in the regions of south Asia, north Africa and the Middle East, and eastern Europe. At the country level, the highest numbers of cumulative excess deaths due to COVID-19 were estimated in India (4·07 million [3·71-4·36]), the USA (1·13 million [1·08-1·18]), Russia (1·07 million [1·06-1·08]), Mexico (798 000 [741 000-867 000]), Brazil (792 000 [730 000-847 000]), Indonesia (736 000 [594 000-955 000]), and Pakistan (664 000 [498 000-847 000]). Among these countries, the excess mortality rate was highest in Russia (374·6 deaths [369·7-378·4] per 100 000) and Mexico (325·1 [301·6-353·3] per 100 000), and was similar in Brazil (186·9 [172·2-199·8] per 100 000) and the USA (179·3 [170·7-187·5] per 100 000).

INTERPRETATION

The full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone. Strengthening death registration systems around the world, long understood to be crucial to global public health strategy, is necessary for improved monitoring of this pandemic and future pandemics. In addition, further research is warranted to help distinguish the proportion of excess mortality that was directly caused by SARS-CoV-2 infection and the changes in causes of death as an indirect consequence of the pandemic.

FUNDING

Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom.

COVID-19 Autopsies Reveal Underreporting of SARS-CoV-2 Infection and Scarcity of Co-infections

Coronavirus disease 2019 (COVID-19) mortality can be estimated based on reliable mortality data. Variable testing procedures and heterogeneous disease course suggest that a substantial number of COVID-19 deaths is undetected. To address this question, we screened an unselected autopsy cohort for the presence of SARS-CoV-2 and a panel of common respiratory pathogens. Lung tissues from 62 consecutive autopsies, conducted during the first and second COVID-19 pandemic waves in Switzerland, were analyzed for bacterial, viral and fungal respiratory pathogens including SARS-CoV-2. SARS-CoV-2 was detected in 28 lungs of 62 deceased patients (45%), although only 18 patients (29%) were reported to have COVID-19 at the time of death. In 23 patients (37% of all), the clinical cause of death and/or autopsy findings together with the presence of SARS-CoV-2 suggested death due to COVID-19. Our autopsy results reveal a 16% higher SARS-CoV-2 infection rate and an 8% higher SARS-CoV-2 related mortality rate than reported by clinicians before death. The majority of SARS-CoV-2 infected patients (75%) did not suffer from respiratory co-infections, as long as they were treated with antibiotics. In the lungs of 5 patients (8% of all), SARS-CoV-2 was found, yet without typical clinical and/or autopsy findings. Our findings suggest that underreporting of COVID-19 contributes substantially to excess mortality. The small percentage of co-infections in SARS-CoV-2 positive patients who died with typical COVID-19 symptoms strongly suggests that the majority of SARS-CoV-2 infected patients died from and not with the virus.

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

The COVID-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighborhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12–0.80%), followed by 2.69% (90% CI 1.88–3.49%) in the second survey and 6.67% (90% CI 5.42–7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25–2.82), while the single best predictor for positivity was ageusia/anosmia (OR 8.12, 95% CI 4.72–13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to adequately describe COVID-19 dispersion in the city. Presented results have helped local government authorities to guide pandemic management.

Excess mortality according to group of causes in the first year of the COVID-19 pandemic in Brazil

ABSTRACT Objective: To estimate excess mortality by cause of death in Brazil and states in 2020. Methods: We estimated the expected number of deaths considering a linear trend analysis with the number of deaths between 2015 and 2019 for each group of causes and each federative unit. We calculated standardized mortality ratios (SMR) and 95% confidence intervals for each SMR assuming a Poisson distribution. We performed the analyses in the R program, version 4.1.3. Results: We observed a 19% excess in deaths in 2020 (SMR=1.19; 95%CI=1.18–1.20). The Infectious and Parasitic Diseases group stood out among the defined causes (SMR=4.80; 95%CI 4.78–4.82). The ill-defined causes showed great magnitude in this period (SMR=6.08; 95%CI 6.06–6.10). Some groups had lower-than-expected deaths: respiratory diseases (10% lower than expected) and external causes (4% lower than expected). In addition to the global analysis of the country, we identified significant heterogeneity among the federative units. States with the highest SMR are concentrated in the northern region, and those with the lowest SMR are concentrated in the southern and southeastern regions. Conclusion: Excess mortality occurs during the COVID-19 pandemic. This excess results not only from COVID-19 itself, but also from the social response and the management of the health system in responding to a myriad of causes that already had a trend pattern before it.

Measuring misclassification of Covid-19 as garbage codes: Results of investigating 1,365 deaths and implications for vital statistics in Brazil

The purpose of this article is to quantify the amount of misclassification of the Coronavirus Disease-2019 (COVID-19) mortality occurring in hospitals and other health facilities in selected cities in Brazil, discuss potential factors contributing to this misclassification, and consider the implications for vital statistics. Hospital deaths assigned to causes classified as garbage code (GC) COVID-related cases (severe acute respiratory syndrome, pneumonia unspecified, sepsis, respiratory failure and ill-defined causes) were selected in three Brazilian state capitals. Data from medical charts and forensic reports were extracted from standard forms and analyzed by study physicians who re-assigned the underlying cause based on standardized criteria. Descriptive statistical analysis was performed and the potential impact in vital statistics in the country was also evaluated. Among 1,365 investigated deaths due to GC-COVID-related causes, COVID-19 was detected in 17.3% in the age group 0-59 years and 25.5% deaths in 60 years and over. These GCs rose substantially in 2020 in the country and were responsible for 211,611 registered deaths. Applying observed proportions by age, location and specific GC-COVID-related cause to national data, there would be an increase of 37,163 cases in the total of COVID-19 deaths, higher in the elderly. In conclusion, important undercount of deaths from COVID-19 among GC-COVID-related causes was detected in three selected capitals of Brazil. After extrapolating the study results for national GC-COVID-related deaths we infer that the burden of COVID-19 disease in Brazil in official vital statistics was probably under estimated by at least 18% in the country in 2020.

Excesso de mortalidade segundo grupo de causas no primeiro ano de pandemia de COVID-19 no Brasil

RESUMO Objetivo: Estimar o excesso de mortalidade segundo causa de óbito no Brasil e estados em 2020. Métodos: O número de óbitos esperado foi estimado considerando análise de tendência linear com o número de mortes entre os anos de 2015 e 2019, para cada grupo de causas e cada unidade da federação. Calculamos as razões de mortalidade padronizadas, e os intervalos com 95% de confiança para cada SMR foram calculados assumindo uma distribuição Poisson. As análises foram realizadas no programa R, versão 4.1.3. Resultados: Observamos um excesso de 19% nos óbitos em 2020 (SMR=1,19; IC=1,18–1,20). O grupo de Doenças Infecciosas e Parasitárias obteve maior destaque entre as causas definidas (SMR=4,80; IC95% 4,78–4,82). As causas mal definidas apresentaram grande magnitude neste período (SMR=6,08; IC95% 6,06–6,10). Há, ainda, grupos que apresentaram número de óbitos abaixo do esperado: doenças do aparelho respiratório (10% abaixo do esperado) e causas externas (4% abaixo do esperado). Além da análise global para o país, identificamos grande heterogeneidade entre as unidades da federação. Os estados com maiores SMR estão concentrados na região norte, e os que possuem menores SMR estão concentrados nas regiões sul e sudeste. Conclusões: Há um excesso de mortalidade ocorrendo durante a pandemia de COVID-19. Este excesso é resultado não apenas da COVID-19 em si, mas da resposta social e da gestão do sistema de saúde em responder a uma miríade de causas que já possuíam um ritmo de tendência anterior a ela.

Excess deaths from all causes and by COVID-19 in Brazil in 2020

OBJECTIVE

To estimate the 2020 all-cause and COVID-19 excess mortality according to sex, age, race/color, and state, and to compare mortality rates by selected causes with that of the five previous years in Brazil.

METHODS

Data from the Mortality Information System were used. Expected deaths for 2020 were estimated from 2015 to 2019 data using a negative binomial log-linear model.

RESULTS

Excess deaths in Brazil in 2020 amounted to 13.7%, and the ratio of excess deaths to COVID-19 deaths was 0.90. Reductions in deaths from cardiovascular diseases (CVD), respiratory diseases, and external causes, and an increase in ill-defined causes were all noted. Excess deaths were also found to be heterogeneous, being higher in the Northern, Center-Western, and Northeastern states. In some states, the number of COVID-19 deaths was lower than that of excess deaths, whereas the opposite occurred in others. Moreover, excess deaths were higher in men aged 20 to 59, and in black, yellow, or indigenous individuals. Meanwhile, excess mortality was lower in women, in individuals aged 80 years or older, and in whites. Additionally, deaths among those aged 0 to 19 were 7.2% lower than expected, with reduction in mortality from respiratory diseases and external causes. There was also a drop in mortality due to external causes in men and in those aged 20 to 39 years. Moreover, reductions in deaths from CVD and neoplasms were noted in some states and groups.

CONCLUSION

There is evidence of underreporting of COVID-19 deaths and of the possible impact of restrictive measures in the reduction of deaths from external causes and respiratory diseases. The impacts of COVID-19 on mortality were heterogeneous among the states and groups, revealing that regional, demographic, socioeconomic, and racial differences expose individuals in distinct ways to the risk of death from both COVID-19 and other causes.