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Addressing Data Challenges for Understanding Climate-Sensitive Diseases in Bangladesh: Evidence from Systematic Review and Government Data Repository

Abstract

Background: Understanding the effects of climate change on health outcomes is
crucial for effective policy formulation and intervention strategies. However, in
low- and middle-income countries like Bangladesh, the true extent of these
negative effects remains unexplored due to data scarcity. This study aims to
assess available evidence on climate change-related health outcomes in
Bangladesh, to compare it with actual occurrences, and to explore challenges
related to climate change and health data.

Methods: We first conducted a systematic review to summarize the climate-
sensitive diseases examined in existing literature in Bangladesh. The review
results were then compared with over 2.8 million samples from the government’s
data repository, representing reported cases of climate-sensitive diseases during
2017-2022. This comparison aimed to identify discrepancies between the diseases
currently occurring in Bangladesh related to climate change and available knowledge through existing research. Additionally, we also explored the limitations of the data recorded in the government data repository.

Results: The available literature in Bangladesh covered only a fraction of the total
climate-sensitive diseases recorded in the government data repository. We also
explored several challenges related to available data in the government repository,
which includes inadequate collection of patients’ comprehensive socio-demographic information and the absence of a unique patient identifier.

Conclusion: The findings highlight the pressing requirement to address data
challenges in comprehending climate-sensitive diseases in Bangladesh. It is
imperative to prioritize the digitalization of the healthcare system and implement a unique patient identification number to facilitate accurate tracking and analysis of health-related data.

Keywords: Climate sensitive disease, government data respiratory, systematic
review, Bangladesh.

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