Search

Although floods are well known for promoting the transmission of malaria, not much effort has been put to determine the spatial distribution of this disease at micro-geographical scale in flood prone areas. Therefore, this paper examines the spatial variation of malaria and associated socio-demographic factors in flood-prone areas of Mbire district, Zimbabwe. A cross-sectional household survey was conducted between 2018 and 2019 to collect data on malaria and socio-demographic factors. The study used the Bernoulli model to determine malaria hotspots, i.e. area with high number of cases compared to the surrounding areas. This was followed by a geographically weighted logistic regression model used to explore the spatial variation of malaria cases in relation to socio-demographic factors at household level. Descriptive statistics and chi-square showed that types of house material, water sources and age of the household head had a significant association with malaria cases (p < 0.05). The study has demonstrated that some local communities in flood prone areas experience increased numbers of malaria cases as indicated by one significant cluster (p < 0.05). There was high malaria risk (2.68) in the significant cluster compared to its outside. The GWLM model with water sources and the type of house material as exploratory variables showed the minimum corrected Akaike's Information Criterion compared to other models. Higher level of spatial variability was observed in type of house material (DIFF of criterion = − 5.742) compared to water sources (DIFF of criterion = − 1.064). The coefficients of these two exploratory variables were varying across the study area and significant (t-values ± 1.96) and high in other parts including the identified hotspots. The coefficients of the type of house material ranged from − 1.136 to 1.323. These were higher than those for water sources which were between − 0.781 and 0.605. These results may be used for development and implementation of place-specific malaria intervention strategies in flood prone areas. [ABSTRACT FROM AUTHOR]

Flood preparedness involves building capacities of communities for effective disaster response and recovery. Communities that effectively prepare for disasters can save life and minimise injuries, property damage and any psychological pain/stress associated with hazards. In view of this, the present study assessed the preparedness of riparian communities living in Mbire district, Zimbabwe and identified their capacity building needs. It used a weighted 5-point Likert Scale to quantify 11 preparedness indicators: resource availability; emergency and evacuation plans; early warning systems; flood knowledge/awareness/education, and proofing information; post-flood recovery; risk communication and social capital. Using a mixed approach, data came from a questionnaire survey involving 304 respondents who were selected through cluster sampling, and five focus group discussions that were purposively selected among the riparian communities. Descriptive statistics were used to analyse quantitative data and determine the level of community preparedness on each variable and indicator. A factor analysis was also conducted to identify the underlying factors that either hindered or promoted flood preparedness. Results show that riparian communities are unprepared for flood disasters. They need capacity building in terms of resource mobilisation, evacuation plans, early warnings, flood education/training/awareness, flood proofing information, post flood recovery and risk communication. A huge majority of about 82% of the indicators showed incipient levels of development. Likewise, about 71% of the variables were at or below incipient level of development. Poverty, flood awareness, social capital and contigency planning emerged as the major drivers of flood preparedness. The study concludes that measuring flood preparedness of riparian communities require context-specific variables. These findings are useful to national and sub-national governments with the mandate to formulate and implement appropriate flood disaster policies and plans where floods are a problem. [ABSTRACT FROM AUTHOR]

Flood risk studies remain focused on understanding causation, impacts, perceptions and coping and adaptation measures and there remain many inappropriate measures taken to reduce household risk. Through a case study approach, this study assessed rural household vulnerability to flooding which helped to determine the level of risk to flood hazards in Mbire District of Zimbabwe. Three hundred and thirty-five (335) households were randomly selected to participate in the survey. The composite index approach was used to calculate vulnerability and risk indices. Results indicated that more than 70% of the households were highly vulnerable to flooding and about 50% were in the medium to very high categories of flood risk. Household vulnerability was not only a question of the natural flood event, but a result of the intersection of poor socio-economic conditions and the physical exposure to floods. The socio-economic determinants of vulnerability included high levels of unemployment resulting in low income and poverty; low levels of education; and over-dependence of the community on rain-fed smallholder farming. Physical exposure of the community mainly resulted from materials used to construct houses. Pole and dagga houses had a higher degree of exposure compared to houses with bricks and cement. Therefore, we recommend that instead of focusing on the whole ward/district the institutional services should first target the most vulnerable and at risk households in order to increase their capacity in dealing with flood hazards. [ABSTRACT FROM AUTHOR]

The study focuses on the impacts of climate variability and change on maize yield in Mt. Darwin District. The rainfall and temperature data for the period under study that is from 1992 to 2012 were obtained from Meteorological Services Department of Zimbabwe at daily resolution while crop yield data were obtained from Department of Agricultural, Technical and Extension Services (AGRITEX) and Zimbabwe Statistics Agency (ZIMSTAT) at seasonal/yearly resolution. In order to capture full rainfall seasons, a year was set to begin on 1 June and end on 31 July the next year. Yearly yield, temperature and rainfall data were used to compute time series analysis of rainfall, temperature and yield. The relationship between temperature, rainfall, quality of season (start, cessation, dry days, wet days and length) and yield was also investigated. The study also investigated the link between meteorological normal and maize yield. The study revealed that temperature is rising while rainfall is decreasing with time hence increasing risk of low maize yield in Mt. Darwin. Correlation between maize yield was higher using a non-linear ( R = 0.630) than a linear regression model ( R = 0.173). There was a very high correlation between maize yield and number of dry days ( R = −0.905) as well as between maize yield and length of season ( R = 0.777). We also observed a strong correlation between percentage normal rainfall and percentage normal maize yield ( R = 0.753). This was also agreed between rainfall tessiles and maize yield tessiles as 50 % of the seasons had normal and above normal rainfall coinciding with normal and above normal maize yield. Of the 21 seasons considered, only one season had above normal rainfall while maize yield was below normal. The study concluded that there is a strong association between meteorological normal and maize yield in a rain-fed agricultural system. Climate information remains crucial to agricultural productivity hence the need to train farmers to access the information and use it for the benefit of their activities. [ABSTRACT FROM AUTHOR]