10 Years of Environmental Change on the Slopes of Mount Kilimanjaro and Its Associated Shift in Malaria Vector Distributions.

INTRODUCTION: Malaria prevalence has declined in the Kilimanjaro region of Tanzania over the past 10 years, particularly at lower altitudes. While this decline has been related to the scale-up of long-lasting insecticidal nets to achieve universal coverage targets, it has also been attributed to changes in environmental factors that are important for enabling and sustaining malaria transmission. OBJECTIVES: Herein, we apply spatial analytical approaches to investigate the impact of environmental and demographic changes, including changes in temperature, precipitation, land cover, and population density, on the range of the major malaria vector species Anopheles arabiensis in two districts of Tanzania, situated on the southern slope of Mount Kilimanjaro. These models are used to identify environmental changes that have occurred over a 10-year period and highlight the implications for malaria transmission in this highland region. METHODS: Entomological data were collected from the Hai and Lower Moshi districts of Tanzania in 2001-2004 and 2014-2015. Vector occurrence data were applied alongside satellite remote sensing indices of climate and land cover, and gridded population data, to develop species distribution models for An. arabiensis for the 2004 and 2014 periods using maximum entropy. Models were compared to assess the relative contribution of different environmental and demographic factors to observed trends in vector species distribution in lowland and highland areas. RESULTS: Changes in land cover were observed in addition to increased population densities, increased warm season temperature, and decreased wetness at low altitudes. The predicted area and extent of suitable habitat for An. arabiensis declined across the study area over the 10-year period, with notable contraction at lower altitudes, while species range in higher altitude zones expanded. Importantly, deforestation and warmer temperatures at higher altitudes may have created stable areas of suitable vector habitat in the highlands capable of sustaining malaria transmission. CONCLUSION: We show that environmental changes have had an important influence on the distribution of malaria vector species in a highland area of northern Tanzania. Highland areas may be at continued risk for sporadic malaria outbreaks despite the overall range contraction of principal vector species at lower altitudes, where malaria transmission remains at low intensity

Mapping clusters of chikungunya and dengue transmission in northern Tanzania using disease exposure and vector data

Background: Dengue and chikungunya are mosquito-borne viral diseases that are of public health importance throughout the tropical and subtropical regions of the world. Seasonal variations in transmission of these viruses have been suggested owing to the ecology of their mosquito vectors. However, little is known about the epidemiology of the diseases Tanzania. To address this gap, seasonal community-based cross-sectional surveys were undertaken to identify potential clusters of transmission in Hai district in northern Tanzania.Methods: Epidemiological and entomological data from two cross-sectional surveys were used to examine the spatial pattern of dengue and chikungunya transmission. Six villages namely, Boma Ng’ombe, Magadini, Rundugai, Nshara and Kware were involved in the study. Serological measures of dengue and chikungunya virus infections were derived using enzyme-linked immunosorbent assays, and all participants were geo-referenced to the household level using a global positioning system. Potential clusters of individual exposed to dengue and chikungunya virus , as well as clusters of Aedes mosquitoes in the wet and dry seasons were detected using SaTScan. All significant clusters (with p≤0.05) were mapped using ArcGIS.Results: A large, widely dispersed cluster of chikungunya exposed individuals was detected spanning Rundugai and parts of Magadini villages (RR = 2.58,  p= 0.01), while no significant clustering was observed in the dry season. Spatial clusters of Aedes aegypti were detected in Rundugai in both the wet and dry seasons (RR = 2.56, p< 0.001 and RR = 2.24, p=0.05, respectively). In the dry season a small cluster was also detected in Kware (RR = 2.25, p=0.05). No significant clusters of dengue were detected in both seasons.Conclusion: Clusters of chikungunya-exposed individuals and Aedes mosquitoes indicate on-going transmission of chikungunya virus in Hai district of northern Tanzania

Increasing capacity in disease vector modelling to improve malaria and arbovirus mitigation strategies : final technical progress report (May 1, 2013 - March 30, 2015)

Species distribution modeling, using MAXENT software, provides a method for monitoring disease vector habitat and species geographic distributions. The project aimed to improve the capacity of researchers at Kilimanjaro Christian Medical University College (KCMUC) and the National Institute for Medical Research (NIMR) in Tanzania, in species distribution modeling to improve vector control strategies. Through workshops and remote collaboration, researchers created maps of malaria, and arboviruses vectors, then used results as a teaching case to transfer these skills. Research partners now have access to ArcGIS (geographic information system); and research partnerships between KCMUC, NIMR, University of Ottawa and HealthBridge were strengthened

Categorical map of predicted malaria prevalence.

<p>Predicted <i>P. falciparum</i> prevalence in children 2 to 9 years old as a function of altitude and vector habitat availability within 1.5 km of grid cells (predicted from niche models) is shown on a categorical scale.</p

Regression model goodness-of-fit.

<p>Area of predicted malaria vector habitat improves the goodness-of-fit of models of malaria prevalence, assessed by regression of observed versus predicted malaria prevalence in children 2 to 9 years old. Assessments were performed for (A) an ordinary least squares regression model of <i>P. falciparum</i> prevalence as a function of altitude, and (B) a conditional autoregressive model of <i>P. falciparum</i> prevalence as a function of altitude and habitat. Data points represent 24 villages in north eastern Tanzania. The 1:1 line is shown for reference.</p

Map of study area in north eastern Tanzania.

<p>Map of study area in north eastern Tanzania.</p

Continuous map of predicted malaria prevalence.

<p>Predicted <i>P. falciparum</i> prevalence in children 2 to 9 years old as a function of altitude and vector habitat availability within 1.5 km of grid cells (predicted from niche models) is shown at 30×30 metre resolution on a continuous scale.</p

Malaria vector niche models.

<p>Models show the area of predicted suitable habitat (shaded area) at a resolution of 30×30 metres across north eastern Tanzania for the dominant malaria vector species, <i>An. arabiensis</i>, <i>An. gambiae</i> s.s. and <i>An. funestus</i> s.l.</p