Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk

Systematic Review on Diversity and Distribution of Anopheles Species in Gabon: A Fresh Look at the Potential Malaria Vectors and Perspectives

Gabon is located in the malaria hyper-endemic zone, where data concerning malaria vector distribution remains fragmentary, making it difficult to implement an effective vector control strategy. Thus, it becomes crucial and urgent to undertake entomological surveys that will allow a better mapping of the Anopheles species present in Gabon. In this review, we examined different articles dealing with Anopheles in Gabon from ProQuest, Web of Science, PubMed, and Google scholar databases. After applying the eligibility criteria to 7543 articles collected from four databases, 42 studies were included that covered a 91-year period of study. The review revealed a wide diversity of Anopheles species in Gabon with a heterogeneous distribution. Indeed, our review revealed the presence of 41 Anopheles species, of which the most abundant were members of the Gambiae and Nili complexes and those of the Funestus and Moucheti groups. However, our review also revealed that the major and minor vectors of malaria in Gabon are present in both sylvatic, rural, and urban environments. The observation of human malaria vectors in sylvatic environments raises the question of the role that the sylvatic environment may play in maintaining malaria transmission in rural and urban areas. Ultimately, it appears that knowledge of biodiversity and spatial distribution of Anopheles mosquitoes is fragmentary in Gabon, suggesting that additional studies are necessary to complete and update these entomological data, which are useful for the implementation of vector control strategies.

Analysis of Health Indicators in Two Rural Communities on the Colombian Caribbean Coast: Poor Water Supply and Education Level Are Associated with Water-Related Diseases

Water-related diseases are closely linked with drinking water, sanitation, and hygiene (WASH) indicators, socioeconomic status, education level, or dwelling's conditions. Developing countries exhibit a particular vulnerability to these diseases, especially rural areas and urban slums. This study assessed socioeconomic features, WASH indicators, and water-related diseases in two rural areas of the Colombian Caribbean coast. Most of this population did not finish basic education (72.3%, N = 159). Only one of the communities had a water supply (aqueduct), whereas the other received water via an adapted tanker ship. No respondents reported sewage services; 92.7% (N = 204) had garbage service. Reported cases of diarrhea were associated with low education levels (P = 2.37 × 10-9) and an unimproved drinking water supply (P = 0.035). At least one fever episode was reported in 20% (N = 44) of dwellings, but the cases were not related to any indicator. The Aedes/House index (percentage of houses that tested positive for Aedes larvae and/or pupae) was 69%, the container index (percentage of water-holding containers positive for Aedes larvae or pupae) 29.4%, and the Breteau index (number of positive containers per 100 houses in a specific location) was three positive containers per 100 inspected houses. The presence of positive containers was associated with the absence of a drinking water supply (P = 0.04). The community with poorer health indicators showed greater health vulnerability conditions for acquisition of water-related diseases. In summary, water supply and educational level were the main factors associated with the presence of water-related diseases in both communities.

Ecosystem Research Experience with Two Indigenous Communities of Colombia: The Ecohealth Calendar as a Participatory and Innovative Methodological Tool

Eco-bio-social factors may increase or decrease a community's susceptibility to vector-borne disease transmission. Traditional studies have contributed information about the association between eco-bio-social factors and health outcomes, but few have provided this information in an integrative way characterizing annual dynamics among indigenous communities. Transdisciplinary research was conducted with the Bari of Karikachaboquira and the Wayúu of Marbacella and El Horno, using qualitative and participatory methods, including seasonal graphics, semi-structured interviews, geo-referencing routes, and participatory observation. The information was triangulated and discussed with local actors in order to validate and complement the results. An ecohealth calendar was obtained for each community, linking the socioecological dynamics to specific diseases, especially malaria. Local dynamics can change, depending on environmental conditions, and these determine the presence or absence of diseases. For both communities, the rainy season is the period with the greatest proliferation of mosquitoes (including Anopheles spp.), during which malaria cases occur. The ecohealth calendar integrates eco-bio-social information from local communities, through participatory and potentially empowering processes, into a comprehensive layout. This can break down the conceptual, demographic, and cultural barriers in the context of community-based interventions and research to action based on an ecosystem framework.

Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence

The long-term goal of the global effort to tackle malaria is national and regional elimination and eventually eradication. Fine scale multi-temporal mapping in low malaria transmission settings remains a challenge and the World Health Organisation propose use of surveillance in elimination settings. Here, we show how malaria incidence can be modelled at a fine spatial and temporal resolution from health facility data to help focus surveillance and control to population not attending health facilities. Using Namibia as a case study, we predicted the incidence of malaria, via a Bayesian spatio-temporal model, at a fine spatial resolution from parasitologically confirmed malaria cases and incorporated metrics on healthcare use as well as measures of uncertainty associated with incidence predictions. We then combined the incidence estimates with population maps to estimate clinical burdens and show the benefits of such mapping to identifying areas and seasons that can be targeted for improved surveillance and interventions. Fine spatial resolution maps produced using this approach were then used to target resources to specific local populations, and to specific months of the season. This remote targeting can be especially effective where the population distribution is sparse and further surveillance can be limited to specific local areas.

Tailoring the visual communication of climate projections for local adaptation practitioners in Germany and the UK

Visualizations are widely used in the communication of climate projections. However, their effectiveness has rarely been assessed among their target audience. Given recent calls to increase the usability of climate information through the tailoring of climate projections, it is imperative to assess the effectiveness of different visualizations. This paper explores the complexities of tailoring through an online survey conducted with 162 local adaptation practitioners in Germany and the UK. The survey examined respondents' assessed and perceived comprehension (PC) of visual representations of climate projections as well as preferences for using different visualizations in communicating and planning for a changing climate. Comprehension and use are tested using four different graph formats, which are split into two pairs. Within each pair the information content is the same but is visualized differently. We show that even within a fairly homogeneous user group, such as local adaptation practitioners, there are clear differences in respondents' comprehension of and preference for visualizations. We do not find a consistent association between assessed comprehension and PC or use within the two pairs of visualizations that we analysed. There is, however, a clear link between PC and use of graph format. This suggests that respondents use what they think they understand the best, rather than what they actually understand the best. These findings highlight that audience-specific targeted communication may be more complex and challenging than previously recognized.

Predictability of epidemic malaria under non-stationary conditions with process-based models combining epidemiological updates and climate variability

Background

Previous studies have demonstrated the feasibility of early-warning systems for epidemic malaria informed by climate variability. Whereas modelling approaches typically assume stationary conditions, epidemiological systems are characterized by changes in intervention measures over time, at scales typically longer than inter-epidemic periods. These trends in control efforts preclude simple application of early-warning systems validated by retrospective surveillance data; their effects are also difficult to distinguish from those of climate variability itself.

Methods

Rainfall-driven transmission models for falciparum and vivax malaria are fitted to long-term retrospective surveillance data from four districts in northwest India. Maximum-likelihood estimates (MLEs) of model parameters are obtained for each district via a recently introduced iterated filtering method for partially observed Markov processes. The resulting MLE model is then used to generate simulated yearly forecasts in two different ways, and these forecasts are compared with more recent (out-of-fit) data. In the first approach, initial conditions for generating the predictions are repeatedly updated on a yearly basis, based on the new epidemiological data and the inference method that naturally lends itself to this purpose, given its time-sequential application. In the second approach, the transmission parameters themselves are also updated by refitting the model over a moving window of time.

Results

Application of these two approaches to examine the predictability of epidemic malaria in the different districts reveals differences in the effectiveness of intervention for the two parasites, and illustrates how the ‘failure’ of predictions can be informative to evaluate and quantify the effect of control efforts in the context of climate variability. The first approach performs adequately, and sometimes even better than the second one, when the climate remains the major driver of malaria dynamics, as found for Plasmodium vivax for which an effective clinical intervention is lacking. The second approach offers more skillful forecasts when the dynamics shift over time, as is the case of Plasmodium falciparum in recent years with declining incidence under improved control.

Conclusions

Predictive systems for infectious diseases such as malaria, based on process-based models and climate variables, can be informative and applicable under non-stationary conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-015-0937-3) contains supplementary material, which is available to authorized users.