Spatial-Explicit Modeling of Social Vulnerability to Malaria in East Africa.

Despite efforts in eradication and control, malaria remains a global challenge, particularly affecting vulnerable groups. Despite the recession in malaria cases, previously malaria free areas are increasingly confronted with epidemics as a result of changing environmental and socioeconomic conditions. Next to modeling transmission intensities and probabilities, integrated spatial methods targeting the complex interplay of factors that contribute to social vulnerability are required to effectively reduce malaria burden. We propose an integrative method for mapping relative levels of social vulnerability in a spatially explicit manner to support the identification of intervention measures. Based on a literature review, a holistic risk and vulnerability framework has been developed to guide the assessment of social vulnerability to water-related vector-borne diseases (VBDs) in the context of changing environmental and societal conditions. Building on the framework, this paper applies spatially explicit modeling for delineating homogeneous regions of social vulnerability to malaria in eastern Africa, while taking into account expert knowledge for weighting the single vulnerability indicators. To assess the influence of the selected indicators on the final index a local sensitivity analysis is carried out. Results indicate that high levels of malaria vulnerability are concentrated in the highlands, where immunity within the population is currently low. Additionally, regions with a lack of access to education and health services aggravate vulnerability. Lower values can be found in regions with relatively low poverty, low population pressure, low conflict density and reduced contributions from the biological susceptibility domain. Overall, the factors characterizing vulnerability vary spatially in the region. The vulnerability index reveals a high level of robustness in regard to the final choice of input datasets, with the exception of the immunity indicator which has a marked impact on the composite vulnerability index. We introduce a conceptual framework for modeling risk and vulnerability to VBDs. Drawing on the framework we modeled social vulnerability to malaria in the context of global change using a spatially explicit approach. The results provide decision makers with place-specific options for targeting interventions that aim at reducing the burden of the disease amongst the different vulnerable population groups

Patterns of spatial genetic structures in Aedes albopictus (Diptera: Culicidae) populations in China.

BACKGROUND:The Asian tiger mosquito, Aedes albopictus, is one of the 100 worst invasive species in the world and the vector for several arboviruses including dengue, Zika and chikungunya viruses. Understanding the population spatial genetic structure, migration, and gene flow of vector species is critical to effectively preventing and controlling vector-borne diseases. Little is known about the population structure and genetic differentiation of native Ae. albopictus in China. The aim of this study was to examine the patterns of the spatial genetic structures of native Ae. albopictus populations, and their relationship to dengue incidence, on a large geographical scale. METHODS:During 2016-2018, adult female Ae. albopictus mosquitoes were collected by human landing catch (HLC) or human-bait sweep-net collections in 34 localities across China. Thirteen microsatellite markers were used to examine the patterns of genetic diversity, population structure, and gene flow among native Ae. albopictus populations. The correlation between population genetic indices and dengue incidence was also examined. RESULTS:A total of 153 distinct alleles were identified at the 13 microsatellite loci in the tested populations. All loci were polymorphic, with the number of distinct alleles ranging from eight to sixteen. Genetic parameters such as PIC, heterozygosity, allelic richness and fixation index (FST) revealed highly polymorphic markers, high genetic diversity, and low population genetic differentiation. In addition, Bayesian analysis of population structure showed two distinct genetic groups in southern-western and eastern-central-northern China. The Mantel test indicated a positive correlation between genetic distance and geographical distance (R2 = 0.245, P = 0.01). STRUCTURE analysis, PCoA and GLS interpolation analysis indicated that Ae. albopictus populations in China were regionally clustered. Gene flow and relatedness estimates were generally high between populations. We observed no correlation between population genetic indices of microsatellite loci in Ae. albopictus populations and dengue incidence. CONCLUSION:Strong gene flow probably assisted by human activities inhibited population differentiation and promoted genetic diversity among populations of Ae. albopictus. This may represent a potential risk of rapid spread of mosquito-borne diseases. The spatial genetic structure, coupled with the association between genetic indices and dengue incidence, may have important implications for understanding the epidemiology, prevention, and control of vector-borne diseases

Climate information for public health : a curriculum for best practices : putting principles to work

The mission of the IRI is to enhance society’s capability to understand, anticipate and manage the impacts of climate in order to improve human welfare and the environment, especially in developing countries. The IRI conducts this mission through strategic and applied research, education, capacity building, and by providing forecasts and information products with an emphasis on practical and verifiable utility and partnership

Childhood malaria case incidence in Malawi between 2004 and 2017:Spatio-temporal modelling of climate and non-climate factors

Introduction Malaria transmission is influenced by a complex interplay of factors including climate, socio-economic, environmental factors and interventions. Malaria control efforts across Africa have shown a mixed impact. Climate driven factors may play an increasing role with climate change. Efforts to strengthen routine facility-based monthly malaria data collection across Africa create an increasingly valuable data source to interpret burden trends and monitor control programme progress. A better understanding of the association with other climatic and non-climatic drivers of malaria incidence over time and space may help guide and interpret the impact of interventions. Methods Routine monthly paediatric outpatient clinical malaria case data were compiled from 27 districts in Malawi between 2004 and 2017, and analysed in combination with data on climatic, environmental, socio-economic and interventional factors and district level population estimates. A spatio-temporal generalized linear mixed model was fitted using Bayesian inference, in order to quantify the strength of association of the various risk factors with district-level variation in clinical malaria rates in Malawi, and visualised using maps. Results Between 2004 and 2017 reported childhood clinical malaria case rates showed a slight increase, from 50 to 53 cases per 1000 population, with considerable variation across the country between climatic zones. Climatic and environmental factors, including average monthly air temperature and rainfall anomalies, normalized difference vegetative index (NDVI) and RDT use for diagnosis showed a significant relationship with malaria incidence. Temperature in the current month and in each of the 3 months prior showed a significant relationship with the disease incidence unlike rainfall anomaly which was associated with malaria incidence at only three months prior. Estimated risk maps show relatively high risk along the lake and Shire valley regions of Malawi. Conclusion Our modelling approach can identify locations likely to have unusually high or low risk of malaria incidence across Malawi, and distinguishes between contributions to risk that can be explained by measured risk-factors and unexplained residual spatial variation. Also, spatial statistical methods applied to readily available routine data provides an alternative information source that can supplement survey data in policy development and implementation to direct surveillance and intervention efforts

Vulnerability and One Health assessment approaches for infectious threats from a social science perspective:a systematic scoping review

Vulnerability assessments identify vulnerable groups and can promote effective community engagement in responding to and mitigating destabilising events. This scoping review maps assessments for local-level vulnerabilities in the context of infectious threats. We searched various databases for articles written between 1978 and 2019. Eligible documents assessed local-level vulnerability, focusing on infectious threats and antimicrobial resistance. Since few studies provided this dual focus, we included tools from climate change and disaster risk reduction literature that engaged the community in the assessment. We considered studies using a One Health approach as essential for identifying vulnerability risk factors for zoonotic disease affecting humans. Of the 5390 records, we selected 36 articles for review. This scoping review fills a gap regarding vulnerability assessments by combining insights from various approaches: local-level understandings of vulnerability involving community perspectives; studies of social and ecological factors relevant to exposure; and integrated quantitative and qualitative methods that make generalisations based on direct observation. The findings inform the development of new tools to identify vulnerabilities and their relation to social and natural environments

Summer Institute on Climate Information for Public Health 2010

Now that the world’s attention is focused on climate variability and climate change adaptation, it is essential, not only for public health communities, but also for planners in central government, to understand the role climate plays in driving disease burden and impacting economic growth. Public health emerges as the final common pathway for all impacts of climate variability and climate change on individuals as well as societies

Interpreting predictive maps of disease, highlighting the pitfalls of species distribution models in epidemiology

This is the authors' PDF version of an article published in Geospatial Health© 2014. The definitive version is available at http://geospatialhealth.netThe application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps). These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread) can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.This work was supported by the Medical Research Council (PMA, NAW - projects G0902445 and MR/J012343/1). The funders had no role in the decision to publish or in preparation of the manuscript

Can the intake of antiparasitic secondary metabolites explain the low prevalence of hemoparasites among wild Psittaciformes?

Background: Parasites can exert selection pressure on their hosts through effects on survival, on reproductive success, on sexually selected ornament, with important ecological and evolutionary consequences, such as changes in population viability. Consequently, hemoparasites have become the focus of recent avian studies. Infection varies significantly among taxa. Various factors might explain the differences in infection among taxa, including habitat, climate, host density, the presence of vectors, life history and immune defence. Feeding behaviour can also be relevant both through increased exposure to vectors and consumption of secondary metabolites with preventative or therapeutic effects that can reduce parasite load. However, the latter has been little investigated. Psittaciformes (parrots and cockatoos) are a good model to investigate these topics, as they are known to use biological control against ectoparasites and to feed on toxic food. We investigated the presence of avian malaria parasites (Plasmodium), intracellular haemosporidians (Haemoproteus, Leucocytozoon), unicellular flagellate protozoans (Trypanosoma) and microfilariae in 19 Psittaciformes species from a range of habitats in the Indo-Malayan, Australasian and Neotropical regions. We gathered additional data on hemoparasites in wild Psittaciformes from the literature. We considered factors that may control the presence of hemoparasites in the Psittaciformes, compiling information on diet, habitat, and climate. Furthermore, we investigated the role of diet in providing antiparasitic secondary metabolites that could be used as self-medication to reduce parasite load. Results: We found hemoparasites in only two of 19 species sampled. Among them, all species that consume at least one food item known for its secondary metabolites with antimalarial, trypanocidal or general antiparasitic properties, were free from hemoparasites. In contrast, the infected parrots do not consume food items with antimalarial or even general antiparasitic properties. We found that the two infected species in this study consumed omnivorous diets. When we combined our data with data from studies previously investigating blood parasites in wild parrots, the positive relationship between omnivorous diets and hemoparasite infestation was confirmed. Individuals from open habitats were less infected than those from forests. Conclusions: The consumption of food items known for their secondary metabolites with antimalarial, trypanocidal or general antiparasitic properties, as well as the higher proportion of infected species among omnivorous parrots, could explain the low prevalence of hemoparasites reported in many vertebrates

Exploratory Analysis of Dengue Fever Niche Variables within the Río Magdalena Watershed

Previous research on Dengue Fever have involved laboratory tests or study areas with less diverse temperature and elevation ranges than is found in Colombia; therefore, preliminary research was needed to identify location specific attributes of Dengue Fever transmission. Environmental variables derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) satellites were combined with population variables to be statistically compared against reported cases of Dengue Fever in the Río Magdalena watershed, Colombia. Three-factor analysis models were investigated to analyze variable patterns, including a population, population density, and empirical Bayesian estimation model. Results identified varying levels of Dengue Fever transmission risk, and environmental characteristics which support, and advance, the research literature. Multiple temperature metrics, elevation, and vegetation composition were among the more contributory variables found to identify future potential outbreak locations