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This study investigated the long-term relationship and causal impact of infectious diseases on food poverty in Benue State, Nigeria, using annual data from 1991 to 2022. It analysed the population in food poverty against the number of people infected with HIV, tuberculosis, hepatitis B virus, malaria fever, and typhoid fever. Employing various econometric methods, including cointegration and Granger causality tests, the research found a stable long-run equilibrium between these variables. The findings indicate that infectious diseases have a positive and significant impact, increasing the number of people experiencing food poverty. Specific diseases like HIV, tuberculosis, hepatitis B virus, malaria, and typhoid fever were all shown to exacerbate food poverty in the region.
This research highlights the critical link between public health and food security. Understanding how infectious diseases worsen food poverty can inform integrated policy responses, helping governments and organisations develop more effective strategies to protect vulnerable populations and improve overall well-being in affected regions.
The abstract focuses on policy recommendations for governments, such as strengthening disease prevention, integrating health and agricultural policies, and improving rural healthcare. It does not indicate any direct commercial applications, products, or services that could be developed from this research.
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Infectious diseases have become a global health challenge which threatens food production and agricultural activities leading to food insecurity and food poverty worldwide. The aim of this study is to empirically examine cointegration and causality inferences of the impact of infectious diseases on the population of people in food poverty in Benue State of Nigeria. The study employed annual secondary time series data from 1991-2022 on the population of people in food poverty as dependent variable and the number of persons infected with infectious diseases like HIV, tuberculosis, hepatitis B virus (HBV), malaria fever and typhoid fever as independent variables. The study employed Augmented Dickey-Fuller (ADF) unit root test, Johansen cointegration test, cointegrating regression analysis, vector error correction model (VECM) and Granger causality test as methods of investigation. The results show that all the study variables become stationary after first differencing. The study found a long-run stable equilibrium relationship among the study variables, implying that the variables share a common stochastic trend and is likely to move together over time without drifting apart. The cointegrating regression analysis reveals that infectious diseases have positive and significant impacts on the population of people in food poverty in Benue State. The findings of this study showed that HIV, tuberculosis, hepatitis B virus, malaria fever and typhoid fever increase the number of people suffering from food poverty in Benue State of Nigeria. The vector error correction model produced a high speed of adjustment of 99.99% towards achieving a long-run equilibrium state annually. The Granger causality tests indicate that all the infectious diseases studied significantly influence food poverty in Benue State. HIV was also found to Granger caused TB and hepatitis B virus (HBV) in Benue state. Feedback causality existed between malaria fever and typhoid fever in the study area. To combat infectious diseases and food insecurity, it is recommended that governments should strengthen disease prevention, integrate health and agricultural policies, improve rural healthcare, implement targeted food security programmes, and establish community-based disease surveillance systems for early outbreak response.
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DOI: 10.56557/ajrmms/2025/v7i189
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