JOURNAL PAPER

1. Taylor Chin, Michael A. Johansson, Anir Chowdhury, Shayan Chowdhury, Kawsar Hosan, Md Tanvir Quader, Caroline O. Buckee & Ayesha S. Mahmud, Bias in mobility datasets drives divergence in modeled outbreak dynamics, Nature Communications Medicine, 5, 1, pp.8, 2025. doi: https://doi.org/10.1038/s43856-024-00714-5

We show that mobility sources can vary significantly in their coverage of travel routes and geographic mobility patterns. Differences in projected outbreak dynamics are more pronounced at finer spatial scales, especially if the outbreak is seeded in smaller and/or geographically isolated regions. In some instances, a simple diffusion (gravity) model was better able to capture the timing and spatial spread of the outbreak compared to the sparser mobility sources.

 

2. Ayesha Sania , Ayesha S. Mahmud, Daniel M. Alschuler, Tamanna Urmi, Shayan Chowdhury, Seonjoo Lee, Shabnam Mostari, Forhad Zahid Shaikh, Kawsar Hosain Sojib, Tahmid Khan, Yiafee Khan, Anir Chowdhury, Shams el Arifeen, Risk factors for COVID-19 mortality among telehealth patients in Bangladesh: A prospective cohort study, PLOS Global Public Health, 2023. doi: https://doi.org/10.1371/journal.pgph.0001971

Estimating the contribution of risk factors of mortality due to COVID-19 is particularly important in settings with low vaccination coverage and limited public health and clinical resources. Very few studies of risk factors of COVID-19 mortality used high-quality data at an individual level from low- and middle-income countries (LMICs). We examined the contribution of demographic, socioeconomic and clinical risk factors of COVID-19 mortality in Bangladesh, a lower middle-income country in South Asia.

 

3. Elizabeth T Rogawski McQuade, PhD Isobel M Blake, PhD Stephanie A Brennhofer, MPH Md Ohedul Islam, MS Syed Shahnewaj Siraj Sony, MS Tonima Rahman, MS Md Hamim Bhuiyan, MS Sabrina Karim Resha, MS Erin G Wettstone, BS Lauren Hughlett, BS Claire Reagan,, Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (December, 2019–December, 2021), The Lancet Microbe, Volume 4, Issue 6, 2023. doi: https://doi.org/10.1016/S2666-5247(23)00010-1

Clinical surveillance for COVID-19 has typically been challenging in low-income and middle-income settings. From December, 2019, to December, 2021, we implemented environmental surveillance in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmission across different income levels of the city compared with clinical surveillance.

 

4. Erin G Wettstone, Md Ohedul Islam, Lauren Hughlett, Claire Reagen, Tahmina Shirin, Mahbubur Rahman, Kawsar Hosan, Md Raihanul Hoque, Stephanie A Brennhofer, Elizabeth T Rogawski McQuade, Yoann Mira, Lukas von Tobel, Rashidul Haque, Mami Taniuchi, Isobe, Interactive SARS-CoV-2 dashboard for real-time geospatial visualisation of sewage and clinical surveillance data from Dhaka, Bangladesh: a tool for public health situational awareness, BMJ Global Health, Volume 8, Issue 8, 2023. doi: http://dx.doi.org/10.1136/bmjgh-2023-012921

Throughout the COVID-19 pandemic, many dashboards were created to visualise clinical case incidence. Other dashboards have displayed SARS-CoV-2 sewage data, largely from countries with formal sewage networks. However, very few dashboards from low-income and lower-middle-income countries integrated both clinical and sewage data sets. We created a dashboard to track in real-time both COVID-19 clinical cases and the level of SARS-CoV-2 virus in sewage in Dhaka, Bangladesh. The development of this dashboard was a collaborative iterative process with Bangladesh public health stakeholders to include specific features to address their needs. The final dashboard product provides spatiotemporal visualisations of COVID-19 cases and SARS-CoV-2 viral load at 51 sewage collection sites in 21 wards in Dhaka since 24 March 2020. Our dashboard was updated weekly for the Bangladesh COVID-19 national task force to provide supplemental data for public health stakeholders making public policy decisions on mitigation efforts. Here, we highlight the importance of working closely with public health stakeholders to create a COVID-19 dashboard for public health impact. In the future, the dashboard can be expanded to track trends of other infectious diseases as sewage surveillance is increased for other pathogens.

 

5. Md. Nabir Hossain, Kawsar Hosan, Md. Saiful Arefin, The Impact of Banking on Economic Growth in Bangladesh: An Empirical study, The Jahangirnagar Economic Review, 32, 1, pp.35, 2021.

The banking sector is crucial to any country's economic progress since it provides capital formation and funding for economic activities. Using yearly data from 2000 to 2021, this paper evaluates the effect of the banking industry of Bangladesh's economic growth. The study examines the data using variables of banking indicators such as bank domestic lending to the private sector, liquidity reserve to bank asset ratio, gross domestic savings, interest rate spread, and deposit interest rate. When utilizing the ordinary least square regression (OLS) approach, some banking variables, such as gross domestic savings and domestic loans to the private sector, have a significant influence on economic growth. Deposit interest rates have a positive but insignificant impact on economic growth. The impact of bank liquidity reserves and interest rate spreads on economic development has a negative but significant effect on economic growth.

 

6. Ayesha S. Mahmud, Shayan Chowdhury, Kawsar Hossain Sojib, Anir Chowdhury, Md. Tanvir Quader, Sangita Paul, Md. Sheikh Saidy, Ramiz Uddin, Kenth Engø-Monsen, Caroline Buckee, Participatory syndromic surveillance as a tool for tracking COVID-19 in Bangladesh, medRxiv, Volume 35, 2020. doi: https://doi.org/10.1016/j.epidem.2021.100462

Limitations in laboratory diagnostic capacity and reporting delays have hampered efforts to mitigate and control the ongoing coronavirus disease 2019 (COVID-19) pandemic globally. To augment traditional lab and hospital-based surveillance, Bangladesh established a participatory surveillance system for the public to self-report symptoms consistent with COVID-19 through multiple channels. Here, we report on the use of this system, which received over 3 million responses within two months, for tracking the COVID-19 outbreak in Bangladesh. Although we observe considerable noise in the data and initial volatility in the use of the different reporting mechanisms, the self-reported syndromic data exhibits a strong association with lab-confirmed cases at a local scale. Moreover, the syndromic data also suggests an earlier spread of the outbreak across Bangladesh than is evident from the confirmed case counts, consistent with predicted spread of the outbreak based on population mobility data. Our results highlight the usefulness of participatory syndromic surveillance for mapping disease burden generally, and particularly during the initial phases of an emerging outbreak.

 

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OTHER

1. Ramiz Uddin; Asad-Uz-Zaman; Anowarul Arif Khan; Meghla Mahmud; Kawsar Hossain Sojib; Iffat Ahamed, Pippa Streeter Hurle; Christine Kelly; Laura Litvine; Chuck Chua; Alexander Whitefield, Encouraging businesses to learn about formal apprenticeship programmes, The Behavioural Insights Team, 2020.
2. Asif Uddin Ahmed, Asad-Uz-Zaman, Kawsar Hossain Sojib, Future Skills: Finding Emerging Skills to Tackle the Challenges of Automation in Bangladesh, a2i Bangladesh, 2018.
3. Sangita Paul (UNDP), Anir Chowdhury (UNDP), Kawsar Hossain Sojib (Jahangirnagar University) and Tara Min Ju Lee (UNDP), Participatory syndromic surveillance tool for the early prediction of COVID-19 outbreak in Bangladesh, UNDP Global Policy Network Brief, 2022.

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