Quantifying the Impact of Climate Change on Mortality Rates: A Stochastic Actuarial Approach in Uganda

Authors

  • Joseph Mubiru

DOI:

https://doi.org/10.47604/jsar.2902

Abstract

Purpose: The aim of the study was to analyze the quantifying the impact of climate change on mortality rates: a stochastic actuarial approach in Uganda.

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: The study found that climate change significantly increases mortality rates, particularly through the rise in extreme weather events and temperature-related illnesses. Using stochastic actuarial models, the research demonstrated a strong correlation between climate variability and higher mortality, especially among vulnerable populations such as the elderly and those with pre-existing health conditions. The findings underscore the urgent need for climate adaptation strategies in Uganda's public health planning to mitigate the adverse effects of climate change on mortality.

Unique Contribution to Theory, Practice and Policy: Risk theory, ecological theory & actuarial life table theory may be used to anchor future studies on analyze the quantifying the impact of climate change on mortality rates: a stochastic actuarial approach in Uganda. Practitioners should integrate climate data into actuarial models used for mortality forecasting and risk assessment. Policymakers should develop and enforce regulatory standards that require the inclusion of climate change considerations in actuarial assessments and reporting.

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Published

2024-08-28

How to Cite

Mubiru, J. (2024). Quantifying the Impact of Climate Change on Mortality Rates: A Stochastic Actuarial Approach in Uganda. Journal of Statistics and Actuarial Research, 8(3). https://doi.org/10.47604/jsar.2902

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Articles