The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013-2020: a Bayesian autoregressive model

F1000Res. 2024 Jun 21:12:1507. doi: 10.12688/f1000research.138859.2. eCollection 2023.

Abstract

Background: Tuberculosis is one of the diseases that requires comprehensive treatment. This disease is highly contagious and can be transmitted through the air. Climate factors play a role in the increasing cases of tuberculosis. This study aimed to determine the correlation between climatic variables and TB in Kolaka District, Southeast Sulawesi Province, Indonesia.

Methods: This research was modeled using an autoregressive (AR) Bayesian model with three possible likelihoods; Gaussian, Poisson and Negative Binomial responses.

Results: Minimum temperature and average temperature, a coefficient of 4.234 suggests that for every 1 degree increase in minimum temperature, there is an estimated increase of approximately four cases, assuming other variables remain constant. Maximum temperature, a coefficient of 17.851 suggests that for every 1 degree increase in maximum temperature, there is an estimated increase of around 17-18 cases, assuming other variables remain constant. Humidity, a coefficient of -13.413 suggests that for every 1% increase in humidity, there is an estimated decrease of around 13 cases, assuming other variables remain constant. Rainfall, a coefficient of -0.327 suggests that for every 1 mm increase in rainfall, there is an estimated decrease of around 0.327 cases, assuming other variables remain constant. Light, a coefficient of -4.322 suggests that for every 1-hour increase in light duration, there is an estimated decrease of around four cases, assuming other variables remain constant.

Conclusions: Climate change has a significant impact on tuberculosis through temperature-related factors. These factors influence the prevalence, spread, and vulnerability to TB. Addressing these challenges requires a holistic approach involving adaptation planning. Strong public health systems and healthcare infrastructure can help mitigate the risks and impacts of climate change-related tuberculosis.

Keywords: Humidity; Indonesia; Light; Rainfall; Temperature; Tuberculosis.

MeSH terms

  • Bayes Theorem*
  • Climate Change
  • Climate*
  • Humans
  • Humidity
  • Indonesia / epidemiology
  • Temperature
  • Tuberculosis* / epidemiology

Associated data

  • figshare/10.6084/m9.figshare.24329518.v1

Grants and funding

The author(s) declared that no grants were involved in supporting this work.