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<p>Climate change is widely recognized as a key driver of vector-borne diseases. However, empirical evidence on its interaction with socioeconomic factors remains inconclusive, particularly in developing countries. This study examines the short- and long-run relationships between climatic, demographic, and economic factors and the incidence of malaria and dengue across five Asian countries—Bangladesh, India, Indonesia, Pakistan, and the Philippines—over the period 2001–2024. Using a balanced panel dataset, we employ a structured econometric approach that begins with Fixed Effects (FE) estimation as the benchmark and extends to panel Autoregressive Distributed Lag (ARDL) and nonlinear ARDL (NARDL) models to capture dynamic adjustment and potential asymmetries. The results provide consistent evidence of long-run equilibrium relationships for both diseases, as indicated by the negative and statistically significant error correction terms. However, the strength and clarity of the long-run determinants differ across diseases. For malaria, the long-run coefficients are generally not statistically significant, suggesting that the equilibrium relationship is not driven by identifiable individual factors. In contrast, dengue exhibits a more robust association with economic conditions, with GDP showing a positive and statistically significant long-run effect on dengue incidence. Short-run dynamics are generally weak and statistically insignificant for both diseases, indicating that changes in temperature, population, and GDP do not produce immediate and consistent impacts on disease incidence in the short run. The nonlinear NARDL specification reveals limited evidence of asymmetrical effects. While a small number of asymmetric relationships are detected, primarily in population dynamics, these effects are not robust across variables or between short-run and long-run specifications. Overall, the findings suggest that disease dynamics in the region are primarily characterized by gradual long-run adjustment rather than short-run fluctuations, and that linear models capture the main empirical patterns more parsimoniously than nonlinear alternatives. These results highlight the importance of long-term structural factors in shaping disease incidence and suggest that policy interventions should prioritize sustained improvements in public health infrastructure and environmental management over short-term reactive measures.</p>

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Exploring climate and economic factors in disease incidence: insights from developing countries of Asia

  • 期刊论文

  • 发表日期：

    2026年5月22日

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  • Mohammad Sharif Karimi,
  • Arooba Iqbal,
  • Yousaf Ali Khan,
  • Huseyin Utku Demir

摘要

Climate change is widely recognized as a key driver of vector-borne diseases. However, empirical evidence on its interaction with socioeconomic factors remains inconclusive, particularly in developing countries. This study examines the short- and long-run relationships between climatic, demographic, and economic factors and the incidence of malaria and dengue across five Asian countries—Bangladesh, India, Indonesia, Pakistan, and the Philippines—over the period 2001–2024. Using a balanced panel dataset, we employ a structured econometric approach that begins with Fixed Effects (FE) estimation as the benchmark and extends to panel Autoregressive Distributed Lag (ARDL) and nonlinear ARDL (NARDL) models to capture dynamic adjustment and potential asymmetries. The results provide consistent evidence of long-run equilibrium relationships for both diseases, as indicated by the negative and statistically significant error correction terms. However, the strength and clarity of the long-run determinants differ across diseases. For malaria, the long-run coefficients are generally not statistically significant, suggesting that the equilibrium relationship is not driven by identifiable individual factors. In contrast, dengue exhibits a more robust association with economic conditions, with GDP showing a positive and statistically significant long-run effect on dengue incidence. Short-run dynamics are generally weak and statistically insignificant for both diseases, indicating that changes in temperature, population, and GDP do not produce immediate and consistent impacts on disease incidence in the short run. The nonlinear NARDL specification reveals limited evidence of asymmetrical effects. While a small number of asymmetric relationships are detected, primarily in population dynamics, these effects are not robust across variables or between short-run and long-run specifications. Overall, the findings suggest that disease dynamics in the region are primarily characterized by gradual long-run adjustment rather than short-run fluctuations, and that linear models capture the main empirical patterns more parsimoniously than nonlinear alternatives. These results highlight the importance of long-term structural factors in shaping disease incidence and suggest that policy interventions should prioritize sustained improvements in public health infrastructure and environmental management over short-term reactive measures.