Iddisah Alhassah

Despite the scale-up of intervention, malaria remains a burden in the Upper River Region of The Gambia. Climate changes and non-climatic conditions can substantially influence malaria prevalence, and further affect the coverage of preventive interventions. This work aimed at exploring the different climatic and non-climatic risk factors associated with malaria. A descriptive research method using a parallel mixed method approach was adopted. Using a multistage approach, 381 households were selected from the region, and primary data was collected from household heads. Descriptive statistics were performed using StataSE18, and the significant influence of environmental and socioeconomic factors was analyzed using Chi-square (Χ2). Thematic analysis for the qualitative part was carried out using Nvivo. Malaria is heavily influenced by rainfalls, floods, and some of the measured non-climatic factors. These results will provide individuals, professionals, government, and policymakers valuable information for better-targeting malaria control efforts.

Impacts of climate change on climate-vulnerable populations receive little attention in the literature compared to the general population across the globe, including Ghana’s Northern Region, than it has on the availability, sources, and kinds of climate services. Understanding the level of effects of utilizing climate information on farmers’ livelihoods is important for climate policy evaluation. Therefore, this study investigates how farmers in three climate-vulnerable groups in Ghana’s Northern Region make adaptation decisions based on climate information. Using a concurrent nested mixed research (quantitative and qualitative) approach, we collected data from 384 sampled farm household respondents, focus group discussions, and experts’ (Key-informants) opinions on climate change in the region. We analyze the data using descriptive statistics and a probit model. The results of mean statistics indicate that whereas farmers across climate-vulnerability groups perceived climate change and variability, the less climate-vulnerable group utilized more climate information for adaptation 7.1 than their counterparts, 5.2 and 3.3 for moderate to high vulnerability, respectively. Also, the probit model result reveals that farmers in the three climate-vulnerable groups are negatively associated with utilizing climate information in their adoption of adaptation strategies for floods and droughts, but they are positively and significantly influenced by climate information in their decision to implement early planting and pest/disease control. Furthermore, although the results show that using climate information boosts farmers’ chances of getting credit by 102.5%, there is no significant chance that farmers would be able to get credit without climate information. The study concludes that, to a greater extent, climate information significantly influences farmers’ decisions regarding adaptation strategies in the region.