BackgroundRwanda reported significant reductions in malaria burden following scale up of control intervention from 2005 to 2010. This study sought to; measure malaria prevalence, describe spatial malaria clustering and investigate for malaria risk factors among health-centre-presumed malaria cases and their household members in Eastern Rwanda.MethodsA two-stage health centre and household-based survey was conducted in Ruhuha sector, Eastern Rwanda from April to October 2011. At the health centre, data, including malaria diagnosis and individual level malaria risk factors, was collected. At households of these Index cases, a follow-up survey, including malaria screening for all household members and collecting household level malaria risk factor data, was conducted.ResultsMalaria prevalence among health centre attendees was 22.8%. At the household level, 90 households (out of 520) had at least one malaria-infected member and the overall malaria prevalence for the 2634 household members screened was 5.1%. Among health centre attendees, the age group 5–15 years was significantly associated with an increased malaria risk and a reported ownership of ≥4 bednets was significantly associated with a reduced malaria risk. At the household level, age groups 5–15 and >15 years and being associated with a malaria positive index case were associated with an increased malaria risk, while an observed ownership of ≥4 bednets was associated with a malaria risk-protective effect. Significant spatial malaria clustering among household cases with clusters located close to water- based agro-ecosystems was observed.ConclusionsMalaria prevalence was significantly higher among health centre attendees and their household members in an area with significant household spatial malaria clustering. Circle surveillance involving passive case finding at health centres and proactive case detection in households can be a powerful tool for identifying household level malaria burden, risk factors and clustering.

We investigate the short-term effects of air temperature, rainfall, and socioeconomic indicators on malaria incidence across Rwanda and Uganda from 2002 to 2011. Delayed and nonlinear effects of temperature and rainfall data are estimated using generalised additive mixed models with a distributed lag nonlinear specification. A time series cross-validation algorithm is implemented to select the best subset of socioeconomic predictors and to define the degree of smoothing of the weather variables. Our findings show that trends in malaria incidence agree well with variations in both temperature and rainfall in both countries, although factors other than climate seem to play an important role too. The estimated short-term effects of air temperature and precipitation are nonlinear, in agreement with previous research and the ecology of the disease. These effects are robust to the effects of temporal correlation. The effects of socioeconomic data are difficult to ascertain and require further evaluation with longer time series. Climate-informed models had lower error estimates compared to models with no climatic information in 77 and 60% of the districts in Rwanda and Uganda, respectively. Our results highlight the importance of using climatic information in the analysis of malaria surveillance data, and show potential for the development of climateinformed malaria early warning systems. IntroductionDespite the global contraction in range over the past century , malaria still imposes a significant health and socioeconomic burden to many countries (WHO, 2013). The World Health Organization estimates that about 3.4 billion people are at risk of malaria (WHO, 2013). Approximately 207 million cases and 627,000 deaths occurred in 2012 worldwide (WHO, 2013). About 90% of the total mortality occurs in sub-Saharan Africa, and 77% of that percentage happens in children under 5 years of age (WHO, 2013). Two countries significantly affected by malaria are Rwanda and Uganda. Malaria has long been considered the main cause of morbidity and mortality in both countries (NISR, MOH and ICF International, 2012; UBOS and ICF International, 2012). Over the period 2002 to 2011, more than five million malaria cases were reported in Rwanda to government health facilities. The number was significantly greater in Uganda with about 100 million reports of suspected malaria cases between 2002 and 2010.Trends in malaria incidence could be attributed to the complex interplay of a range of determinants including climatic, environmental, and socioeconomic factors (Kazembe et al., 2006;Lowe et al., 2013;Rulisa et al., 2013). Statistical models are useful tools that allow us: i) to understand how disease outcomes change as a function of variations in their key driver; and ii) to predict disease outcomes based on the dynamics of such drivers (James et al., 2013). This paper aims to investigate the ways in which malaria incidence varies as a function of short-term changes in air temperature and rainfall over the period [2002][2003][2004][2005][...

Despite the decline in malaria incidence due to intense interventions, potentials for malaria transmission persist in Rwanda. To eradicate malaria in Rwanda, strategies need to expand beyond approaches that focus solely on malaria epidemiology and also consider the socioeconomic, demographic and biological/disease-related factors that determine the vulnerability of potentially exposed populations. This paper analyses current levels of social vulnerability to malaria in Rwanda by integrating a set of weighted vulnerability indicators. The paper uses regionalisation techniques as a spatially explicit approach for delineating homogeneous regions of social vulnerability to malaria. This overcomes the limitations of administrative boundaries for modelling the trans-boundary social vulnerability to malaria. The utilised approach revealed high levels of social vulnerability to malaria in the highland areas of Rwanda, as well as in remote areas where populations are more susceptible. Susceptibility may be due to the populations' lacking the capacity to anticipate mosquito bites, or lacking resilience to cope with or recover from malaria infection. By highlighting the most influential indicators of social vulnerability to malaria, the applied approach indicates which vulnerability domains need to be addressed, and where appropriate interventions are most required. Interventions to improve the socioeconomic development in highly vulnerable areas could prove highly effective, and provide sustainable outcomes against malaria in Rwanda. This would ultimately increase the resilience of the population and their capacity to better anticipate, cope with, and recover from possible infection. IntroductionDespite various interventions to reduce the burden of malaria, the disease persists in many countries of the developing world. In 2012 there were approximately 562,000 malaria deaths in Africa, despite a slow decline since 2004 (WHO, 2014. Malaria decrease in Sub-Saharan Africa was generally associated with intense interventions and reduced vector density due to changing rainfall patterns (Meyrowitsch et al., 2011). Although considerable progress has been made in many countries, the general malaria burden remains high, particularly in young children and pregnant women (Roll Back Malaria, 2005). The Plasmodium (P.) falciparum prevalence rates in Rwanda increased until the late 1990s and early 2000s, after which a marked decrease was noted (Stern et al., 2011). Since 2004, interventions to prevent and control malaria in Rwanda have resulted in a substantial decline in malaria transmission, particularly as a result of improved access to effective treatment, increased use of bed nets, and indoor residual spraying (Karema et al., 2012). However, malaria incidence increased again between 2011 and 2012, revealing the fragility of the gains achieved (WHO, 2013). The results of an entomological survey of more than 50% exophile entomological inoculation rate (EIR) around Kigali City is also an indicator of potential transmission ga...

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