Impact of Climate Change on Public Health and Adaptation Policies: Bangladesh Perspective
Bibliographic record
Abstract
Evidence suggests that global climate change tends to have several adverse effects on public health in near future, mainly among the poorest population of the developing countries. Bangladesh has already experienced some of the severe impacts because of its climate characteristics, geographical location and conditions, combined with high population density and poor health infrastructure. Recently, many of those climate events have made the health impacts much worse due to newer environmental threats, such as changes in eco-climate, salinity intrusion in soil and water and internal displacement of population. This paper aims to identify some of the direct and indirect impacts of climate change on public health condition of Bangladesh. To identify such impacts, primary and secondary sources of information have been widely reviewed. It has been seen that health problems and hazards induced by climate change have been gaining importance of Bangladesh since last decade; however, there is still lack of research and capacity in this field. Linkage between climate change and increased incidences of diseases, rate of mortality, and availability of safe water has not yet received proper focus. Climate change has a potential adverse impact on human health in Bangladesh. The magnitude of malaria, dengue, childhood diarrhoea, and pneumonia as well as malnutrition are found high among the vulnerable communities. Moreover, health safety issues have come forward as deaths from drowning and snake bite during the extreme weather have eventually increased. Health problems, health-climate change links, and contextual issues like healthcare access, expenditure and poverty have been reported. Prevention and control of climate sensitive diseases need to be addressed with area-specific interventions guided by local-level planning of the low-income vulnerable communities. Community based adaptation strategy for health could be beneficial to minimize climate change attributed health burden of Bangladesh. Mugda Med Coll J. 2025; 8(2): 157-163
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".