ABSTRACT
Objective: The aim of this study was to estimate the proportion of symptomatic and asymptomatic laboratory-confirmed coronavirus disease 2019 (COVID-19) cases among the population of Bangladesh. Methods: A cross-sectional survey was conducted in Dhaka City and other districts of Bangladesh between April 18 and October 12, 2020. A total of 32 districts outside Dhaka were randomly selected, and one village and one mahalla was selected from each district; 25 mahallas were selected from Dhaka City. From each village or mahalla, 120 households were enrolled through systematic random sampling. Results: A total of 44 865 individuals were interviewed from 10 907 households. The majority (70%, n = 31 488) of the individuals were <40 years of age. Almost half of the individuals (49%, n = 21 888) reported more than four members in their household. It was estimated that 12.6% (n = 160) of the households had one or more severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals, among whom 0.9% (n = 404) of individuals had at least one COVID-19-like symptom, at the national level. The prevalence of COVID-19 in the general population was 6.4%. Among the SARS-CoV-2-positive individuals, 87% were asymptomatic. Conclusions: The substantial high number of asymptomatic cases all over Bangladesh suggests that community-level containment and mitigation measures are required to combat COVID-19. Future studies to understand the transmission capability could help to define mitigation and control measures.
ABSTRACT
To date, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected over 80 million people globally. We report a case series of five clinically and laboratory confirmed COVID-19 patients from Bangladesh who suffered a second episode of COVID-19 illness after 70 symptom-free days. The International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), is a leading public health research institution in South Asia. icddr, b staff were actively tested, treated and followed-up for COVID-19 by an experienced team of clinicians, epidemiologists, and virologists. From 21 March to 30 September 2020, 1370 icddr,b employees working at either the Dhaka (urban) or Matlab (rural) clinical sites were tested for COVID-19. In total, 522 (38%) were positive; 38% from urban Dhaka (483/1261) and 36% from the rural clinical site Matlab (39/109). Five patients (60% male with a mean age of 41 years) had real-time reverse transcription-polymerase chain reaction (rRT-PCR) diagnosed recurrence (reinfection) of SARS-CoV-2. All had mild symptoms except for one who was hospitalized. Though all cases reported fair risk perceptions towards COVID-19, all had potential exposure sources for reinfection. After a second course of treatment and home isolation, all patients fully recovered. Our findings suggest the need for COVID-19 vaccination and continuing other preventive measures to further mitigate the pandemic. An optimal post-recovery follow-up strategy to allow the safe return of COVID-19 patients to the workforce may be considered.
ABSTRACT
Cholera, a devastating diarrheal disease that caused several global pandemics in the last centuries, may share some similarities with the new COVID-19. Cholera has affected many populations in history and still remains a significant burden in developing countries. The main transmission route was thought to be predominantly through contaminated drinking water. However, revisiting the historical data collected during the Copenhagen 1853 cholera outbreak allowed us to re-evaluate the role of drinking-water transmission in a city-wide outbreak and reconsider some critical transmission routes, which have been neglected since the time of John Snow. Recent empirical and cohort data from Bangladesh also strengthened the dynamic potentiality of other transmission routes (food, fomite, fish, flies) for transmitting cholera. Analyzing this particular nature of the cholera disease transmission, this paper will describe how the pattern of transmission routes are similar to COVID-19 and how the method of revisiting old data can be used for further exploration of new and known diseases.