a b s t r a c tRecent trends in abrupt weather changes continue to pose a challenge to agricultural production most especially in sub-Saharan Africa. The paper specifically addresses the questions on how local farmers read and predict the weather; and how they can collaborate with weather scientists in devising adaptation strategies for climate variability (CV) in the Okavango Delta of Botswana. Recent trends in agriculture-related weather variables available from country's climate services, as well as in freely available satellite rainfall products were analysed. The utility of a seasonal hydrological forecasting system for the study area in the context of supporting farmer's information needs were assessed. Through a multi-stage sampling procedure, a total of 592 households heads in 8 rural communities in the Okavango Delta were selected and interviewed using open and close-ended interview schedules. Also, 19 scientists were purposively selected and interviewed using questionnaires. Key informant interviews, focus group and knowledge validation workshops were used to generate qualitative information from both farmers and scientists. Descriptive and inferential statistics were used in summarising the data. Analysis of satellite rainfall products indicated that there was a consistent increase in total annual rainfall throughout the region in the last 10 years, accompanied by an increase in number of rain days, and reduction of duration of dry spells. However, there is a progressive increase in the region's temperatures leading to increase in potential evaporation. Findings from social surveys show that farmers' age, education level, number of years engaged in farming, sources of weather information, knowledge of weather forecasting and decision on farming practices either had a significant relationship or correlation with their perceptions about the nature of both local [ethno-meteorological] and scientific weather knowledge. Nonetheless, there was a significant difference in the mean scores of farmers in relation to their perceptions and those of the climate scientists about the nature of both local and Western knowledge. As farmers are adept at judging seasonal patterns through long-standing ethno-meteorology, one major CV adaptation measure is their ability to anticipate changes in future weather conditions, which enables them to adjust their farming calendars and make decisions on crop type selection in any given season.
This study investigated potential risk factors associated with malaria transmission in Tubu village, Okavango subdistrict, a malaria endemic area in northern Botswana. Data was derived from a census questionnaire survey, participatory rural appraisal workshop, field observations, and mosquito surveys. History of malaria episodes was associated with several factors: household income (P < 0.05), late outdoor activities (OR = 7.016; CI = 1.786–27.559), time spent outdoors (P = 0.051), travel outside study area (OR = 2.70; CI = 1.004–7.260), nonpossession of insecticide treated nets (OR = 0.892; CI = 0.797–0.998), hut/house structure (OR = 11.781; CI = 3.868–35.885), and homestead location from water bodies (P < 0.05). No associations were established between history of malaria episodes and the following factors: being a farmer (P > 0.05) and number of nets possessed (P > 0.05). Eave size was not associated with mosquito bites (P > 0.05), frequency of mosquito bites (P > 0.05), and time of mosquito bites (P > 0.05). Possession of nets was very high (94.7%). Close proximity of a health facility and low vegetation cover were added advantages. Some of the identified risk factors are important for developing effective control and elimination strategies involving the community, with limited resources.
Good knowledge on the interactions between climatic variables and malaria can be very useful for predicting outbreaks and preparedness interventions. We investigated clinical malaria transmission patterns and its temporal relationship with climatic variables in Tubu village, Botswana. A 5-year retrospective time series data analysis was conducted to determine the transmission patterns of clinical malaria cases at Tubu Health Post and its relationship with rainfall, flood discharge, flood extent, mean minimum, maximum and average temperatures. Data was obtained from clinical records and respective institutions for the period July 2005 to June 2010, presented graphically and analysed using the Univariate ANOVA and Pearson cross-correlation coefficient tests. Peak malaria season occurred between October and May with the highest cumulative incidence of clinical malaria cases being recorded in February. Most of the cases were individuals aged >5 years. Associations between the incidence of clinical malaria cases and several factors were strong at lag periods of 1 month; rainfall (r = 0.417), mean minimum temperature (r = 0.537), mean average temperature (r = 0.493); and at lag period of 6 months for flood extent (r = 0.467) and zero month for flood discharge (r = 0.497). The effect of mean maximum temperature was strongest at 2-month lag period (r = 0.328). Although malaria transmission patterns varied from year to year the trends were similar to those observed in sub-Saharan Africa. Age group >5 years experienced the greatest burden of clinical malaria probably due to the effects of the national malaria elimination programme. Rainfall, flood discharge and extent, mean minimum and mean average temperatures showed some correlation with the incidence of clinical malaria cases.
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