Institute Of Epidemiology , Disease Control And Research Research Articles

Dengue in Tomorrow: Predictive Insights From ARIMA and SARIMA Models in Bangladesh: A Time Series Analysis.

Dengue fever has been a continued public health problem in Bangladesh, with a recent surge in cases. The aim of this study was to train ARIMA and SARIMA models for time series analysis on the monthly prevalence of dengue in Bangladesh and to use these models to forecast the dengue prevalence for the next 12 months. This secondary data-based study utilizes AutoRegressive Integrated Moving Average (ARIMA) and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models to forecast dengue prevalence in Bangladesh. Data was sourced from the Institute of Epidemiology Disease Control and Research (IEDCR) and the Directorate General of Health Services (DGHS). STROBE Guideline for observational studies was followed for reporting this study. The ARIMA (1,1,1) and SARIMA (1,1,2) models were identified as the best-performing models. The forecasts indicate a steady dengue prevalence for 2024 according to ARIMA, while SARIMA predicts significant fluctuations. It was observed that ARIMA (1,1,1) and SARIMA (1,2,2) (1,1,2) 12 were the most suitable models for prediction of dengue prevalence. These models offer valuable insights for healthcare planning and resource allocation, although external factors and complex interactions must be considered. Dengue prevalence is expected to rise in future in Bangladesh.

Antimicrobial Resistance Surveillance Methods in Bangladesh: Present and Way Forward.

The Institute of Epidemiology, Disease Control and Research (IEDCR) conducts active, case-based national antimicrobial resistance (AMR) surveillance in Bangladesh. The Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project accessed aggregated retrospective data from non-IEDCR study sites and 9 IEDCR sites to understand the pattern and extent of AMR and to use analyzed data to guide ongoing and future national AMR surveillance in both public and private laboratories. Record-keeping practices, data completeness, quality control, and antimicrobial susceptibility test practices were investigated in all laboratories participating in case-based IEDCR surveillance and laboratory-based CAPTURA sites. All 9 IEDCR laboratories recorded detailed case-based data (n = 16 816) in electronic format for a priority subset of processed laboratory samples. In contrast, most CAPTURA sites (n = 18/33 [54.5%]) used handwritten registers to store data. The CAPTURA sites were characterized by fewer recorded variables (such as patient demographics, clinical history, and laboratory findings) with 1 020 197 individual data, less integration of patient records with the laboratory information system, and nonuniform practice of data recording; however, data were collected from all available clinical samples. The analyses conducted on AMR data collected by IEDCR and CAPTURA in Bangladesh provide current data collection status and highlight opportunities to improve ongoing data collection to strengthen current AMR surveillance system initiatives. We recommend a tailored approach to conduct AMR surveillance in high-burden, resource-limited settings.

Tackling a global epidemic threat: Nipah surveillance in Bangladesh, 2006-2021.

Human Nipah virus (NiV) infection is an epidemic-prone disease and since the first recognized outbreak in Bangladesh in 2001, human infections have been detected almost every year. Due to its high case fatality rate and public health importance, a hospital-based Nipah sentinel surveillance was established in Bangladesh to promptly detect Nipah cases and respond to outbreaks at the earliest. The surveillance has been ongoing till present. The hospital-based sentinel surveillance was conducted at ten strategically chosen tertiary care hospitals distributed throughout Bangladesh. The surveillance staff ensured that routine screening, enrollment, data, and specimen collection from suspected Nipah cases were conducted daily. The specimens were then processed and transported to the reference laboratory of Institute of Epidemiology, Disease Control and Research (IEDCR) and icddr,b for confirmation of diagnosis through serology and molecular detection. From 2006 to 2021, through this hospital-based surveillance platform, 7,150 individuals were enrolled and tested for Nipah virus. Since 2001, 322 Nipah infections were identified in Bangladesh, 75% of whom were laboratory confirmed cases. Half of the reported cases were primary cases (162/322) having an established history of consuming raw date palm sap (DPS) or tari (fermented date palm sap) and 29% were infected through person-to-person transmission. Since the initiation of surveillance, 68% (218/322) of Nipah cases from Bangladesh have been identified from various parts of the country. Fever, vomiting, headache, fatigue, and increased salivation were the most common symptoms among enrolled Nipah patients. Till 2021, the overall case fatality rate of NiV infection in Bangladesh was 71%. This article emphasizes that the overall epidemiology of Nipah virus infection in Bangladesh has remained consistent throughout the years. This is the only systematic surveillance to detect human NiV infection globally. The findings from this surveillance have contributed to early detection of NiV cases in hospital settings, understanding of Nipah disease epidemiology, and have enabled timely public health interventions for prevention and containment of NiV infection. Although we still have much to learn regarding the transmission dynamics and risk factors of human NiV infection, surveillance has played a significant role in advancing our knowledge in this regard.

Temporal dynamics and fatality of SARS-CoV-2 variants in Bangladesh.

Since the beginning of the SARS-CoV-2 pandemic, multiple new variants have emerged posing an increased risk to global public health. This study aimed to investigate SARS-CoV-2 variants, their temporal dynamics, infection rate (IFR) and case fatality rate (CFR) in Bangladesh by analyzing the published genomes. We retrieved 6610 complete whole genome sequences of the SARS-CoV-2 from the GISAID (Global Initiative on Sharing all Influenza Data) platform from March 2020 to October 2022, and performed different in-silico bioinformatics analyses. The clade and Pango lineages were assigned by using Nextclade v2.8.1. SARS-CoV-2 infections and fatality data were collected from the Institute of Epidemiology Disease Control and Research (IEDCR), Bangladesh. The average IFR was calculated from the monthly COVID-19 cases and population size while average CFR was calculated from the number of monthly deaths and number of confirmed COVID-19 cases. SARS-CoV-2 first emerged in Bangladesh on March 3, 2020 and created three pandemic waves so far. The phylogenetic analysis revealed multiple introductions of SARS-CoV-2 variant(s) into Bangladesh with at least 22 Nextstrain clades and 107 Pangolin lineages with respect to the SARS-CoV-2 reference genome of Wuhan/Hu-1/2019. The Delta variant was detected as the most predominant (48.06%) variant followed by Omicron (27.88%), Beta (7.65%), Alpha (1.56%), Eta (0.33%) and Gamma (0.03%) variant. The overall IFR and CFR from circulating variants were 13.59% and 1.45%, respectively. A time-dependent monthly analysis showed significant variations in the IFR (p = 0.012, Kruskal-Wallis test) and CFR (p = 0.032, Kruskal-Wallis test) throughout the study period. We found the highest IFR (14.35%) in 2020 while Delta (20A) and Beta (20H) variants were circulating in Bangladesh. Remarkably, the highest CFR (1.91%) from SARS-CoV-2 variants was recorded in 2021. Our findings highlight the importance of genomic surveillance for careful monitoring of variants of concern emergence to interpret correctly their relative IFR and CFR, and thus, for implementation of strengthened public health and social measures to control the spread of the virus. Furthermore, the results of the present study may provide important context for sequence-based inference in SARS-CoV-2 variant(s) evolution and clinical epidemiology beyond Bangladesh.

Case Investigation, Contact Tracing and Containment Prevents Spread of COVID-19 in Shibchar, Madaripur, Bangladesh 2020: An Evidence Based Observational Study

Background: In December 2019, the COVID-19 pandemic began in Wuhan and quickly spread in China and other countries in the world. The SARS-CoV-2 virus reached Bangladesh in March 2020 and the index case of the first cluster of COVID-19 was reported on 13 March, 2020, in Madaripur District.
 Methods: A team from the Institute of Epidemiology, Disease Control and Research (IEDCR), of Ministry of Health and Family Welfare, Bangladesh investigated the cluster, established active syndromic surveillance for respiratory diseases, and implemented control activities.
 Results: The index case traveled from Italy to Bangladesh and developed respiratory symptoms and sought medical treatment in Dhaka. He was diagnosed with COVID-19 and transferred and isolated in a hospital on the day of diagnosis. We followed up his contacts as soon as we got their names and contact information. We quarantined 34 among 139 contacts, rest of them were missed contacts. The attack rate among the index cases’ contacts was 18% (6/34). Eight cases in Madaripur District with COVID-19 were epidemiologically linked to the index case. The most common symptoms were fever (100%) and cough (86%). One case was asymptomatic. The Bangladesh influenza pandemic containment plan was modified for COVID-19 mitigation which included establishing a containment zone, mobilizing the local administrative authorities, and obtaining support from local community, religious and political leaders. Active case search in the containment zone identified new cases. No new cases were linked with the nine COVID-19 cases.
 Conclusion: Active surveillance by health authority, prompt isolation of cases, quarantine of contacts and establishing a containment zone to focus mitigation efforts supported the prevention efforts for further transmission of the virus from this first COVID-19 cluster in Bangladesh.

The viral etiology of acute febrile illness of in Dhaka, Bangladesh in the year of 2017

BackgroundThis is sometimes a challenge to identify the etiologies of acute febrile illnesses (AFI) due to non-specific clinical presentation as well as limited availability of diagnostic facilities. Bangladesh is very much suitable for vector borne viral infections like Dengue, Chikungunya and Zika due to hot and humid climate. MethodIn 2017 during the period of April to November there was an outbreak of febrile illness in Dhaka city, the capital of Bangladesh. With the aim to explore the situation Institute of Epidemiology, Disease Control and Research (IEDCR) took an initiative to investigate the etiology of febrile illness. Sixteen hundred and thirty two patients with history of acute onset of fever with or without arthalgia and rash, who attended to IEDCR,were tested for Dengue, Chikungunya and Zika by multiplex PCR. ResultsAmong them 66%, 7% and 0.4% were positive for Chikungunya, Dengue and co-infected with both pathogens respectively. Dengue virus positive serum samples were further analyzed for serotyping and found re-emergence of DEN-3 in the circulation along with existing serotypes DEN-1 and DEN-2. ConclusionConsidering the climatic condition and existence of domestic and peri-domestic setup in Bangladesh correlates with persistent mosquito breeding and survival as well as transmissibility of vector borne viral diseases. Thus continuous surveillance is required from public health point of view for prevention and control of arboviral diseases in Bangladesh.

Accuracy comparison of ARIMA and XGBoost forecasting models in predicting the incidence of COVID-19 in Bangladesh.

Accurate predictive time series modelling is important in public health planning and response during the emergence of a novel pandemic. Therefore, the aims of the study are three-fold: (a) to model the overall trend of COVID-19 confirmed cases and deaths in Bangladesh; (b) to generate a short-term forecast of 8 weeks of COVID-19 cases and deaths; (c) to compare the predictive accuracy of the Autoregressive Integrated Moving Average (ARIMA) and eXtreme Gradient Boosting (XGBoost) for precise modelling of non-linear features and seasonal trends of the time series. The data were collected from the onset of the epidemic in Bangladesh from the Directorate General of Health Service (DGHS) and Institute of Epidemiology, Disease Control and Research (IEDCR). The daily confirmed cases and deaths of COVID-19 of 633 days in Bangladesh were divided into several training and test sets. The ARIMA and XGBoost models were established using those training data, and the test sets were used to evaluate each model's ability to forecast and finally averaged all the predictive performances to choose the best model. The predictive accuracy of the models was assessed using the mean absolute error (MAE), mean percentage error (MPE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The findings reveal the existence of a nonlinear trend and weekly seasonality in the dataset. The average error measures of the ARIMA model for both COVID-19 confirmed cases and deaths were lower than XGBoost model. Hence, in our study, the ARIMA model performed better than the XGBoost model in predicting COVID-19 confirmed cases and deaths in Bangladesh. The suggested prediction model might play a critical role in estimating the spread of a novel pandemic in Bangladesh and similar countries.

Adverse Events Following COVID-19 Immunization Reported Through Hotlines, February-August 2021, Bangladesh: Descriptive Study

Background For COVID-19 vaccine safety, the vaccination program of Bangladesh started facility-based passive surveillance to address adverse events following immunization (AEFIs) with COVID-19 vaccination. The Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh, has been using emergency hotlines for outbreak reporting since 2008. During the COVID-19 pandemic, these hotlines are being used for pandemic-related information and reporting. Thus, COVID-19 vaccinees also use these hotlines to report AEFIs. Objective We analyzed the documented AEFIs records of the IEDCR to characterize the vaccinees who reported AEFIs through IEDCR hotlines. Methods We performed a descriptive analysis of COVID-19 vaccinees who reported AEFIs through IEDCR hotlines from February to August 2021. We defined AEFIs as untoward medical occurrences that follow immunization and that do not necessarily have a causal relationship with the usage of the vaccines. We analyzed the vaccinees who reported AEFIs through IEDCR hotlines by age, gender, occupation, the severity of AEFIs, and the time intervals of reporting. Results Of 819 vaccinees who reported AEFIs through IEDCR hotlines, 555 (67.8%) were male and their median age was 41 years (IQR 32-51 years). Of them, 494 (89%) reported AEFIs following the first dose of vaccination. Among females, 186 (70.5%) of 264 were housewives. Among males, 249 (44.9%) of 555 were service holders, 90 (16.2%) were businessmen, and 46 (8.3%) were students. About 638 (77.9%) of 819 vaccinees were from urban vaccination centers. Mild AEFIs, such as fever (508/819, 62%), injection-site pain (336/819, 41%), and headache (205/819, 25%), were reported through IEDCR hotlines. Although 534 (65.2%) of 819 vaccinees who reported AEFIs through IEDCR hotlines developed symptoms within 24 hours of vaccination, only 196 (23.9%) of 819 vaccinees reported them within 24 hours. Conclusions Middle-aged, male, and urban vaccinees who developed mild AEFIs commonly reported AEFIs through IEDCR hotlines. We recommended that AEFI data generated from different reporting systems, including hotline numbers, be incorporated together for an efficient COVID-19 vaccine safety surveillance system.

SECOND WAVE AND PANDEMIC SITUATION OF COVID-(2020-2021) IN BANGLADESH

Background: In Bangladesh, the Institute of Epidemiology, Disease Control and Research (IEDCR) reported the first COVID-19 positive patients in the country on March 8, 2020. The world health organization (WHO) declared a COVID-19 epidemic on March 11, 2020. The aim of this study was related to the situation and relation of tests, infested, recovered and death of people against COVID-19 of Bangladesh. The study was carried out from 8 March 2020 to 30 April 2021 (N=419 days) to observe the status of Bangladesh towards rampant COVID-19. Methods: The data of this research was collected from IEDCR, Directorate General of Health Services (DGHS), Ministry of Health and Family Welfare (MoHFW), and cross-checked with different newspapers and online news portals. Correlations were made using Spearman's rank correlation coefficient. Results: The total tests, infection, recovered and died were 5357294, 747761, 669995 and 11250; respectively in Bangladesh. The tests of COVID-19 were 1482, 69252, 244064, 460528, 409503, 362113, 397452, 389452, 436862, 454892, 424034, 392403 and 722848 in March to December, 2020 to January to April 2021; respectively in Bangladesh. The infestation of COVID-19 was 49, 7616, 39486, 98330, 92125, 73070, 50457, 44205, 57248, 58948, 21629, 11077 and 128555 in March to December, 2020 to January to April 2021; respectively in Bangladesh. The recovered of COVID-19 was 25, 135, 7904, 34845, 76517, 69452, 71600, 48658, 56099, 70367, 22285, 17140 and 150816 in March to December, 2020 to January to April 2021; respectively in Bangladesh. The death of COVID-19 was 6, 163, 472, 1198, 1264, 1125, 970, 666, 718, 938, 568, 277 and 2237 in March to December, 2020 to January to April 2021; respectively in Bangladesh. The maximum number of people infested and death in April, 2021. The positive correlation found between infested with tests and recovered with tests of April, 2021 by people where (R2= 0.5289, p<0.012 and 0.0000006 p<0.05) and the negative correlation found between tests with date and death with tests (R2= 0.2567, p<0.01 and 0.3614, p<0.01). All the Spearman correlation positive with moderate to strong relation between the variables at the 0.01 level in two-tailed and the total number was n=419. The mean Spearman correlation for tests was 0.31 (range 0.553 to 0.634), for infested was 0.35 (range 0.611 to 0.880), for recovered was 0.796 (range 0.634 to 0.799), for death was 0.808 (range 0.553 to 0.880). March to December 2020 and January to February 2021, not much less than April 2021. Conclusions: More people infested and died in April, 2021 than previous year. This study also indicated that there is moderate to strong relation among tests, infested, recovered and death with COVID-(2020-2021).

Impact of COVID-19 on Public Transportation and Road Safety in Bangladesh.

Due to the spread of COVID-19, global measures such as lockdown and limits on public transit, entertainment, the closure of all educational institutions, and religious practices have been imposed in early 2020. During and after the COVID-19 disease outbreak, the first target ought to be safer road travel and zero fatalities. This paper general overviews the effects of the government’s COVID-19 control measures on Bangladesh’s transportation system and road safety during the period March 2020–2021. Secondary data sources, newspaper articles, WHO, Worldometer, Institute of Epidemiology, Disease Control and Research (IEDCR) websites, and relevant research papers were used to compile this article. The various restriction policies would have a negative impact on the transportation sector’s finances, exacerbating the economic crisis that public transportation and airline operators in Bangladesh are experiencing. This study found that restricting mobility reduces road traffic deaths and injuries by a small amount, but that accidents continue to occur during the lockdown period in Bangladesh.

A Study on Anxiety, Facility, and Protective Measures of Health Professionals of Bangladesh

As part of the worldwide pandemic of SARS-CoV-2 infection, Bangladesh was infected. The firstthree cases were confirmed by the Institute of Epidemiology Disease Control and Research (IEDCR) in the first week of March 2020. The Bangladeshi government immediately required its citizens to comply with the national lockdown to curb the spread of a virus where everyone keeps themselves safe and protected at home except for medical professionals, who risk treating patients in a hospital. This article explores the situation medical professionals go through during the pandemic. This study used a quantitative method with a cross-sectional survey based on frequently asked questions (FAQ). Primary data were obtained from 200 respondents (doctors, nurses, medical professionals). According to the study, the lack of access and availability of PPE such as Particulate Respirator Masks, face shields, protective clothing, protective gloves, and hand sanitizer/disinfectant as facilities in hospitals causes Generalized Anxiety Disorder, Panic Disorder, Social Phobia, and Post-Stress Disorder Trauma from before. However, a positive correlation was found between lack of supply of protective equipment and increased anxiety, panic disorder, social phobia, etc., among healthcare professionals.

Chikungunya Arbovirus in Bangladesh: An Epidemic with Medical Entomology

Background: Chikungunya virus (CHIKV) transmits to humans by infected mosquitoes of Aedes Aegypti and Aedes Albopictus that has been emerged as a serious public health threat globally. In 2017, Dhaka city of Bangladesh experienced an explosive outbreak of chikungunya, an arthropod-borne virus resulting in more than 13,800 clinically confirmed cases. This paper focuses on the pattern of massive outbreak of chikungunya in Dhaka City as well as the association between different entomological indicators and chikungunya infection. Methods: The relevant patient information was principally collected from the Institute of Epidemiology, Disease Control and Research (IEDCR) and Dhaka Medical College and Hospital (DMCH), and entomological surveillance data from the Communicable Disease Control (CDC) of Directorate General of Health Services (DGHS) in Dhaka. In addition, surveys were conducted in localities where an outbreak of CHIKV had occurred. A total of 2708 households were visited and a total of 4767 habitats were characterized. Face-to- face interview process was also employed from 436 confirmed patients. The regression analysis, Odds Ratio (OR), and Relative Risk (RR) were used to analyse the risk factors of entomological indicators in making connotation with chikungunya infection. Spatial mapping with proportional symbology and geostatistics were also employed. Results: The overall chikungunya outbreak in 2017 for Dhaka city shows that about 137 per 100,000 population were infected with CHIKV with the average prevalence rate of 1.11±0.65% (95% CI of 0.97- 1.25). Some 97.3% patients had high-grade fever with an average maximum temperature of 103.9±0.78°F, 88.3% patients declared for deep and sharp myalgia, and almost all the patients (98.6%) reported severe arthralgia in different joints. In addition, the average odds of confirmed chikungunya patients in households were found to be 2.43 times (OR: 2.24-2.70 with 95% CI and P <0.001) and the relative risk was calculated for 2.07 (RR: 1.91-2.24 with 95% CI and P <0.001) times compared to the infections in negative households in Dhaka City. Moreover, the entomological information shows that out of 4767 habitats, some 12.96% were positive for Aedes Aegypti larvae and pupae, and positive correlations were found between different entomological indices and chikungunya infections. Conclusion: Since there is no curative treatment for chikungunya, a proper policy including patient management and Behaviour Change Communication (BCC) as well as strong surveillance strategies should be formulated for the prevention of chikungunya infection as well as to lessen the incidence of mosquito vectors.

Antimicrobial resistance pattern of urinary tract pathogens from tertiary care hospitals in Bangladesh

Background: In Bangladesh, urinary tract infection (UTI) patients usually self-medicate or receive empirical treatment from physicians to start immediate treatment or to avoid expensive medical care. A study of 2016 in Bangladesh showed resistance to antibiotics like quinolones (52%), 3rd generation cephalosporin (51.1%), cotrimoxazole (47%) and imipenem (1%) in UTI. To understand the national situation of antimicrobial resistance (AMR), Institute of Epidemiology, Disease Control and Research (IEDCR), the national institute of epidemiology of Bangladesh, started a surveillance in ten tertiary care hospitals since 2017 from six types of specimens including urine of UTI patients. Objectives of this study were to determine the distribution and antibiotic resistance patterns of UTI pathogens. Methods and materials: We analyzed data of UTI patients enrolled in five initially started sites of AMR surveillance in 2018. UTI patient was defined as >5 years old patient attending outdoor, with abrupt onset of frequency of micturition & urgency with fever, chill or burning sensation of urine or loin pain. Epidemiological data and urine sample were collected. Sample were tested for routine microscopy examination and antimicrobial susceptibility test (AST). AST was performed by disc diffusion method following Clinical and Laboratory Standard Institute (CLSI) guideline. We included intermediate and resistant zone in calculation of resistance. Results: In 2018, a total of 1779 UTI patients reported, 439 (24%) had growth in culture. Culture positivity was more in UTI with >5 pus cells/high power field (HPF) (54/439, 80%) on microscopy than <5 pus cells/HPF (85/439, 19%). About 8% patient took antibiotics previously. Culture positive UTI was more in female 323 (73%) than male 116 (26%). Common pathogens were Escherichia coli (57.4%), Klebsiella (17.3%) and Staphylococcus aureus (10.93%). Escherichia coli was resistant 57% to quinolones, 55% to 3rd generation cephalosporin, 54% to cotrimoxazole and 5% to imipenem; Klebsiella was resistant 37% to third generation cephalosporin, 57% to quinolones, 54% to cotrimoxazole and 8.6% to imipenem. Gram negative bacteria also showed resistance to imipenem. Conclusion: Urinary pathogens showed higher resistance against commonly used antibiotics like quinolone, 3rd generation cephalosporin and cotrimoxazole. We recommend to conduct studies on prescription pattern and physicians should be aware about resistance pattern to treat accordingly.

Infection and Death Patterns of COVID-19 Disease in Bangladesh

Objectives: This study aimed to reveal the prevalence of COVID-19 and investigate the patterns of deaths due to novel coronavirus in Bangladesh. Methods: The data about daily incidences, sex and deaths by the geography of COVID-19 for Bangladesh as of August 29, 2020 have been collected from the daily press releases of the Institute of Epidemiology, Disease Control and Research (IEDCR) and Directorate General of Health Services (DGHS). Case fatality rates (CFR), doubling time, correlation coefficient and graphical presentation were used to investigate the prevalence and patterns of infection and deaths. Results: Infection to tests, recovery to infections and death to infection rates due to novel coronavirus in Bangladesh until August 29, 2020 was 20.25%, 64.37% and 1.36% respectively. The correlation coefficient between daily tests and infections has found 0.978 with a 95% confidence interval 0.971 to 0.984. About 78.46% male and only 21.54% of females have died. Most deaths were found in the Dhaka division (48.26%) and the least deaths in the Mymensingh division (2.12%). The sex ratio of males to females in deaths was 364.23%. The age below 10 has found the least prevalent (0.45%) to deaths and above 60 has found most vulnerable (49.26%) to death. Conclusions: This study showed a strong positive relationship between daily tests and infections. The doubling time of infections and deaths in Bangladesh increased over time maintaining very low differences. Male people are more vulnerable to death compare to females. Aged people are extremely vulnerable to death. The most deaths geographical division is Dhaka and the least deaths in Mymensingh.

Use of weekly mobile phone call-unit to screen pregnant women and their newborns for acute respiratory and gastrointestinal illness symptoms in rural Bangladesh

Background/Aims Acute respiratory and gastrointestinal illnesses are major contributors to morbidity and mortality worldwide, particularly in vulnerable populations of pregnant women and infants. It is critical to understand the burden of these illnesses in low-resource settings where infectious, nutritional, and immunotoxicological risk factors overlap and access to medical care may be limited.Methods We established a birth cohort (NCT03930017) at the JiVitA Maternal and Child Health and Nutrition Research Project site in rural Bangladesh enrolling pregnant women during gestational weeks 13-16. In collaboration with the Government of Bangladesh Institute of Epidemiology, Disease Control and Research (IEDCR), we established a mobile phone-based research support system call-center to ascertain acute respiratory and gastrointestinal symptoms in the cohort of pregnant women and their newborns at weekly intervals from study enrollment to 3-months postpartum. Further, if a participant reported acute respiratory illness or influenza-like illness (ILI) symptoms a confirmatory nasal swab specimen was collected, and real time qPCR analysis and subtyping was conducted for influenza types A and B.Results From October 2018 to January 2020, IEDCR completed 24,915 weekly mobile phone call-based interviews with 765 mothers (94% completion rate) and 11,230 weekly call-based interviews with caretakers who described morbidity for 638 infants (93% completion rate). Incident cases of ILI were recorded at a rate of 3.2 per 100 interviews among mothers and 7.7 per 100 interviews for infants. We also observed 1.6 and 1.8 incident cases of diarrhea per 100 interviews among mothers and infants, respectively. 850 nasal swabs were collected for confirmatory RT-qPCR analysis.Conclusions A mobile phone call-unit was established and produced high degree of data completeness in a pregnancy and birth cohort in rural Bangladesh. These longitudinal acute respiratory and gastrointestinal morbidity symptom data can support future planned analyses of associations with biomarkers of co-infections, micronutrient deficiency, and immunotoxicant exposure.

Relationship between Weather Variables and New Daily COVID-19 Cases in Dhaka, Bangladesh

The present study investigated the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman rank correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature, and wind speed with the COVID-19 outbreak in Dhaka, Bangladesh. The study found that, among the seven indicators, only two indicators (minimum temperature and average temperature) had a significant relationship with new COVID-19 cases. The study also found that air quality index (AQI) had a strong negative correlation with cumulative cases of COVID-19 in Dhaka city. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 spread in Dhaka and other countries around the world.

Effect of meteorological factors on COVID-19 cases in Bangladesh.

This work is intended to examine the effects of Bangladesh's subtropical climate on coronavirus diseases 2019 (COVID-19) transmission. Secondary data for daily meteorological variables and COVID-19 cases from March 8 to May 31, 2020, were collected from the Bangladesh Meteorological Department (BMD) and Institute of Epidemiology, Disease Control and Research (IEDCR). Distributed lag nonlinear models, Pearson’s correlation coefficient and wavelet transform coherence were employed to appraise the relationship between meteorological factors and COVID-19 cases. Significant coherence between meteorological variables and COVID-19 at various time–frequency bands has been identified in this work. The results showed that the minimum (MinT) and mean temperature, wind speed (WS), relative humidity (RH) and absolute humidity (AH) had a significant positive correlation while contact transmission had no direct association with the number of COVID-19 confirmed cases. When the MinT was 18 °C, the relative risk (RR) was the highest as 1.04 (95%CI 1.01–1.06) at lag day 11. For the WS, the highest RR was 1.03 (95% CI 1.00–1.07) at lag day 0, when the WS was 21 km/h. When RH was 46%, the highest RR was 1.00 (95% CI 0.98–1.01) at lag day 14. When AH was 23 g/m3, the highest RR was 1.05 (95% CI 1.01–1.09) at lag day 14. We found a profound effect of meteorological factors on SARS-CoV-2 transmission. These results will assist policymakers to know the behavioral pattern of the SARS-CoV-2 virus against meteorological indicators and thus assist to devise an effective policy to fight against COVID-19 in Bangladesh.

Geographical Distribution of COVID-19 Cases and Household Handwashing Practice in Bangladesh: Situation Analysis from National Representative Data

Background: The newly identified Coronavirus disease (COVID-19) has currently expanded and shifted from an epidemic to global pandemic. To date there is no proven vaccine for this contagion, prevention measures are the only option for the world to stay safe. According to the World Health Organization, frequent handwashing with soap for 20 seconds is the most effective prevention measures to reduce the incidence of this global pandemic. Method: Our present study was based on the national presentative publicly available two datasets. One is the latest Multiple Indicator Cluster Survey (MICS 2019) to explore hand washing situation in Bangladesh, another one is the confirmed cases of COVID-19 throughout Bangladesh from Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh as of June 20, 2020. Both data were cross-sectional in nature. Findings: Prevalence of household handwashing was found 56.3%, and the prevalence was significantly varied across the socio-economic status of the households (HH). We observed a higher number of COVID-19 cases (as of June 20, 2020) where there is a relatively lower prevalence of handwashing. Northern part of Bangladesh had the highest handwashing practice whereas it had less effected by COVID-19 cases. However, central Bangladesh had the hardest hit by COVID-19 cases, and it had around 50% handwashing practice coverage. Poorer HHs, low education of the HH heads, HH with no improved water source facility had a strong correlation with not practicing HH handwashing. Interpretation: Around half of Bangladesh does not practice HH level handwashing. Areas where higher the HH handwashing practice, lower the COVID-19 cases were observed.Funding Statement: Authors did not receive any funding for this study.Declaration of Interests: The authors have no conflict of interest to declare.

Exploring Epidemiological Behavior of Novel Coronavirus (COVID-19) Outbreak in Bangladesh.

Globally, there is an obvious concern about the fact that the evolving 2019-nCoV coronavirus is a worldwide public health threat. The appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China at the end of 2019 triggered a major global epidemic, which is now a major community health issue. As of August 13, 2020, according to the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh has reported 269,095 confirmed cases between 8 March and 13 August 2020, with > 1.30% of mortality rate and > 57% of recovery rate. COVID-19 outbreak is evolving so rapidly in Bangladesh; therefore, the availability of epidemiological data and its sensible analysis are essential to direct strategies for situational awareness and intervention. This article presents an exploratory data analysis approach to collect and analyze COVID-19 data on epidemiological outbreaks based on the first publicly available COVID-19 Daily Dataset of Bangladesh. Various publicly open data sources on the outbreak of COVID-19 provided by the IEDCR, World Health Organization (WHO), Directorate General of Health Services (DGHS), and Ministry of Health and Family Welfare (MHFW) of Bangladesh have been used in this research. Visual exploratory data analysis (V-EDA) techniques have been followed in this research to understand the epidemiological characteristics of COVID-19 outbreak in different districts of Bangladesh between 8 March 2020 and 13 August 2020 and these findings were compared with those of other countries. In all, this is extremely important to promptly spread information to understand the risks of this pandemic and begin containment activities in the country.

Rehabilitation Perspectives of COVID-19 Pandemic in Bangladesh

Introduction: The COVID-19 has overwhelmed health systems across the countries globally. This pandemic has also impacted health related rehabilitation services worldwide which is particularly profound in low and middle-income countries including Bangladesh.&#x0D; Methods: Information used in the study gathered from World Health Organization (WHO) Bangladesh Director General of Health Services (DGHS), Institute of Epidemiology Disease Control and Research (IEDCR), online literature search using PubMed and PubMed Central research engines. Information also collected over personal telephone and email correspondence from the selected government, public, corporate, non-government institutes, and rehabilitation personals during the period of March-May 2020. Gathered data were analyzed; a set of challenges identified, and recommendations were made for a safe and standard working rehabilitation environment in the altered COVID-19 situation.&#x0D; Results: Rehabilitation doctors and therapists at most of the public and private institutes are dedicated to COVID-19 services as per the local administrative directives keeping routine rehabilitation services apart. Few rehabilitation workforces to continue team works, environmental hygiene maintenance and space crisis at service outlets were the major challenges. Specially arranged virtual OPD and telerehabilitation services opened to minimize the rehabilitation burden and sufferings of the patient during the COVID-19 pandemic lock down restriction period.&#x0D; Conclusion: COVID-19 seriously impacted the overall schedule of rehabilitation services. Rehabilitation must be recognized as an un-omissible part of COVID-19 management which requires a planned accommodative working environment in the altered situation within the health care system. Recommendations are provided to keep this pandemic contained while providing adequate and standard rehabilitation services to the disabled in the safe environment in line with WHO rehabilitation 2030.&#x0D; J Bangladesh Coll Phys Surg 2020; 38(0): 76-81