Assessment of Excess Mortality and Household Income in Rural Bangladesh During the COVID-19 Pandemic in 2020

Excess mortality during COVID-19 pandemic in Bangladesh - evidence from a rural survey

Background

The coronavirus disease 2019 (COVID-19) had a profound impact worldwide. In Bangladesh, the official number of deaths for COVID-19 was around 29 000. However, many countries including Bangladesh experienced substantial underreporting of COVID-19 deaths due to lack of complete national civil registration system. This study aims to estimate excess mortality in 2020, identify risk factors, and determine leading causes of death in Bangladesh.

Methods

In February 2021, we conducted a cross-sectional household survey in Sitakunda, a subdistrict of Chattogram, identifying deaths from January 2018 to December 2020. Excess mortality was quantified using the p-score and incidence rate ratio (IRR) utilising Poisson segmented regression. We employed the InterVA-5 algorithm to attribute causes of death. Proportional distribution and cause-specific mortality rates (CSMR) per 100 000 individuals were compared between pre-pandemic and pandemic periods.

Results

Among 1748 deaths from 25 669 households, we found 1.4 (95% confidence interval (CI) = 1.2-1.4) times excess mortality in 2020 compared to 2018-2019. Leading causes of death in 2020 included cardiac disease (CSMR = 121.0, CI = 115.8-127.3), stroke (CSMR = 108.0, CI = 102.6-114.0), and acute respiratory infection (CSMR = 61.0, CI = 55.1-66.5), all displaying significantly higher mortality rates than in previous years. Older age (IRR = 1.6), less education (IRR = 1.8), and lower socio-economic groups (IRR = 2.1) had higher mortality rates in 2020 compared to pre-pandemic years.

Conclusion

Our study suggests high rural excess mortality during COVID-19 including cardiac disease, stroke and acute respiratory infection as the leading causes of deaths. We require targeted strategies to identify high-risk patients with comorbidity and social vulnerabilities that contribute to mortality to guide the preparedness strategy for future pandemics.

Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis

BACKGROUND

Although the COVID-19 pandemic claimed a great deal of lives, it is still unclear how it affected mortality in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality during the COVID-19 pandemic in LLMICs, including methods, sources of data, and potential contributing factors that might have influenced excess mortality.

METHODS

We conducted a systematic review and meta-analysis on excess mortality during the COVID-19 pandemic in LLMICs in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus. We included studies published from 2019 onwards with a non-COVID-19 period of at least one year as a comparator. The meta-analysis included studies reporting data on population size, as well as observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals. The protocol was registered in PROSPERO (ID: CRD42022378267).

RESULTS

The review covered 29 countries, with 10 countries included in the meta-analysis. The pooled meta-analysis included 1,405,128,717 individuals, for which 2,152,474 deaths were expected, and 3,555,880 deaths were reported. Calculated excess mortality was 100.3 deaths per 100,000 population per year, with an excess risk of death of 1.65 (95% CI: 1.649, 1.655, p < 0.001). The data sources used in the studies included civil registration systems, surveys, public cemeteries, funeral counts, obituary notifications, burial site imaging, and demographic surveillance systems. The primary techniques used to estimate excess mortality were statistical forecast modelling and geospatial analysis. One out of the 24 studies found higher excess mortality in urban settings.

CONCLUSION

Our findings demonstrate that excess mortality in LLMICs during the pandemic was substantial. However, estimates of excess mortality are uncertain due to relatively poor data. Understanding the drivers of excess mortality, will require more research using various techniques and data sources.

Excess mortality during the COVID-19 pandemic in low-income and lower middle-income countries: protocol for a systematic review and meta-analysis

INTRODUCTION

The COVID-19 pandemic has been marked by a massive death toll. However, the overall effect of the pandemic, including potential unintended negative impacts of some control measures, on mortality remains poorly understood in low-income and lower middle-income countries (LLMICs). This review aims to summarise the available literature on excess mortality in LLMICs, focusing on the methods and data sources used in estimating excess mortality and the drivers of excess mortality.

METHODS AND ANALYSIS

We will review the available literature and report results in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis. Searches will be conducted in PubMed, Embase, Web of Science, Cochrane Library, Google Scholar and Scopus. All published studies that report on the estimates of excess mortality in populations of LLMICs will be included. This will include those with a publication date from 2019 onwards and those with at least a 1-year non-COVID-19 period as the comparator in the estimation of excess mortality during the pandemic. There will be no language restrictions on the search. The meta-analysis will include studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We will use the Mantel-Haenszel method to estimate the pooled risk ratio with 95% CIs.

ETHICS AND DISSEMINATION

As there is no primary data collection, there is no requirement for ethical review. The results will be disseminated through peer-reviewed journal publication and conference presentations.

PROSPERO REGISTRATION NUMBER

CRD42022378267.

Excess mortality during the COVID-19 pandemic (2020-2021) in an urban community of Bangladesh

Measuring COVID-19-related mortality is vital for making public health policy decisions. The magnitude of COVID-19-related mortality is largely unknown in low- and middle-income countries (LMICs), including Bangladesh, due to inadequate COVID-19 testing capacity and a lack of robust civil registration and vital statistics systems. Even with the lack of data, cemetery-based death records in LMICs may provide insightful information on potential COVID-19-related mortality rates; nevertheless, there is a dearth of research employing cemetery-based death records. This study aimed to assess the excess mortality during the COVID-19 pandemic in an urban setting in Bangladesh using a cemetery-based death registration dataset. A total of 6,271 deaths recorded between January 2015 and December 2021 were analysed using a Bayesian structural time series model. Exploratory analysis found that the average monthly number of deaths was 69 during the pre-COVID-19 period (January 2015-February 2020), but significantly increased to 92 during the COVID-19 period (March 2020-December 2021). The increase in male deaths was twice as large as the increase in female deaths. Model-based results were not statistically significant (relative effect 17%, 95% credible interval: -18%, 57%), but there was an overall increasing trend during the COVID-19 period, and specific months or shorter periods had a substantial increase. This first-of-its-kind study in Bangladesh has assessed the excess mortality in an urban community during the COVID-19 pandemic. Cemetery-based death registration appears to aid in tracking population mortality, especially in resource-limited countries where collecting data on the ground is challenging during crisis periods; however, additional large-scale research is required.

Relationship between initial symptoms and the prognosis, sex, and demographic area of patients with COVID-19

Background

A method of determining the initial symptoms and main prognostic identifiers for COVID-19 can be a key tool for physicians, especially primary care physicians. Therefore, the objective of this study was to examine the prognosis of patients with COVID-19 from two different demographic regions according to baseline and main symptoms, age, and sex.

Methods

All individuals selected from both urban and rural health centers were over 18 years of age, had COVID-19 before 2 March 2021, and were followed up with a primary care physician. All patients included in this study were recruited in terms of sex, age at the time of infection, type of contact, baseline symptoms, primary and secondary symptomatology, emergency assistance, hospitalization, intensive care unit (ICU) admission, and death.

Results

A total of 219 and 214 subjects were recruited from rural and urban health centers, respectively. Subjects with COVID-19 from rural areas were significantly older in age, with a higher proportion of men, and had significantly lower baseline and main symptoms than those from urban areas. In addition, the presence of both fever and dyspnea as the initial or main symptom is significantly associated with emergency assistance, hospitalization, and death, regardless of sex, age, and demographic area. This type of illness was reported to be significantly less frequent in the rural population than in the urban population.

Conclusion

The presence of both fever and dyspnea as both initial and main symptoms is a poor prognostic factor for COVID-19, regardless of age, sex, and demographic areas. In addition, women reported lower levels of fever and dyspnea, requiring minimal emergency assistance and fewer hospitalization, and a lower rate of mortality than men. During a COVID-19 infection follow-up, subjects in rural areas seem to have less access to medical care than those in urban areas.