\ud Detection and Monitoring of Insecticide Resistance in Malaria Vectors in Tanzania Mainland\ud

\ud Vector control is a major component of the global strategy for malaria control which aims to prevent parasite transmission mainly through interventions targeting adult Anopheline vectors. Insecticide treated nets (ITNs) and indoor residual spraying (IRS) are the cornerstone of malaria vector control programmes. These major interventions in most cases use pyrethroid insecticides which are also used for agricultural purposes. With widespread development of resistance to pyrethroid insecticides in malaria vectors raises concern over the sustainability of insecticide-based interventions for malaria control. Therefore, close monitoring of performance of the insecticides against malaria vectors is essential for early detection and\ud management of resistance. To measure pyrethroid susceptibility in populations of malaria vectors in Tanzania and to test the efficacy of LLINs/ITNs and insecticide residues on sprayed wall substrates in the IRS operation areas. In 2011 the National Institute for Medical Research (NIMR) in collaboration with National Malaria Control Programme (NMCP) conducted large scale surveillance to determine the countrywide susceptibility levels of malaria vectors to insecticides used for both public health and agricultural purposes. Anopheles gambiae Giles s.l. were collected during national surveys and samples of LLINs/ITNs in the 14 sentinel sites and houses from the IRS areas were randomly selected for bioassays to test the efficacy and insecticide residual effects on sprayed wall substrates respectively. Wild adult mosquitoes for susceptibility testing were collected by resting catches indoors. Net traps (outdoors and indoors) were set up to enhance catches. WHO Susceptibility kits were used to test for resistance status using test papers: Lambdacyhalothrin 0.05%, Deltamethrin 0.05%, Permethrin 0.75%, DDT 4%, Propoxur 0.1% and Fenitrothion 1%. The quality of the test paper was checked against a laboratory susceptible An. gambiae Kisumu strain. Knockdown effect and mortality were measured in standard WHO susceptibility tests and cone bio-efficacy tests. Whereas, con bioassays on treated walls and ITNs were conducted using the laboratory susceptible An. gambiae Kisumu strain. The results from the surveillance recorded continued susceptibility of malaria vectors to commonly used insecticides. However, there were some isolated cases of resistance and/or reduced susceptibility to pyrethroid insecticides which may not compromise the current vector control interventions in the country. Anopheles gambiae s.l. showed resistance (15-28%) to each of the pyrethroids and to DDT but not to Organophosphates (Propoxur 0.1%), and Carbamates (Fenitrothion 1%). The information obtained from this surveillance is expected to be used to guide the National Malaria Control Programme on the rational selection of insecticides for malaria vector control and for the national mitigation plans for management and containment of malaria vector resistance in the country. The current observation warrants more vigilant monitoring of the susceptibility of malaria mosquitoes to commonly used insecticides in areas found with resistance and/or reduced levels of susceptibility of malaria vectors to insecticides, particularly in areas with heavy agricultural and/or public health use of insecticides where resistance is likely to develop. The current survey covered malaria vectors only and not the non malaria vectors (nuisance) mosquitoes such as Culex. Similar monitoring of insecticide susceptibility of this non malaria vectors may be needed to ensure public motivation for sustained use of ITNs/LLINs in the country. The surveillance leading to these results received funding from PMI/USAID through RTI International with Sub Agreement Number 33300212555.\u

Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

Climate change and infectious livestock diseases: The case of Rift Valley fever and tick-borne diseases

Climate change influences the occurrence and transmission of a wide range of livestock diseases through multiple pathways. Diseases caused by pathogens that spent part of their life cycle outside the host (e.g. in vectors or the environment) are more sensitive in this regard, compared to those caused by obligate pathogens. In this chapter, we use two well-studied vector-borne diseases—Rift Valley fever (RVF) and tick-borne diseases (TBDs)—as case studies to describe direct pathways through which climate change influences infectious disease-risk in East and southern Africa. The first case study demonstrates that changes in the distribution and frequency of above-normal precipitation increases the frequency of RVF epidemics. The second case study suggests that an increase in temperature would cause shifts in the spatial distribution of TBDs, with cooler and wetter areas expected to experience heightened risk with climate change. These diseases already cause severe losses in agricultural productivity, food security and socio-economic development wherever they occur, and an increase in their incidence or geographical coverage would intensify these losses. We further illustrate some of the control measures that can be used to manage these diseases and recommend that more research should be done to better understand the impacts of climate change on livestock diseases as well as on the effectiveness of the available intervention measures

Ecological factors associated with rift valley fever during inter-epidemic period in Tanzania

PhD ThesisRift Valley Fever (RVF) is climate-related arboviral disease of livestock and humans. Rift Valley Fever epidemics are associated with dynamics of mosquito abundance. Studies during inter-epidemic periods (IEP) where there is very little or no virus activity pose challenges including where and how to effectively sample vectors and when should the next outbreaks are expected. Entomological surveys were conducted on abundance and distribution of potential RVF vectors in Ngorongoro district of northern Tanzania. Mosquito sampling techniques and timing were also compared to effectively trap vectors. Mosquitoes were sampled both outdoor and indoor using the CDC light traps and Mosquito Magnets. Outdoor traps were placed in proximity with breeding sites and under canopy in banana plantations in proximity to animals sleeping areas. After every three hours, inspection was done on each trap to recover any trapped mosquito. Traps were set repeatedly in each area for three consecutive days and nights during the study period. All mosquitoes collected were sorted according to site of collection, type of trap and time of collection. Mosquito species were identified morphologically using specific keys. After morphological identification, mosquitoes were kept on ice during transportation to laboratory. Data from this study was used in ecological niche modelling experiment using maximum entropy (MaxEnt) to predict distributions of vectors (Aedes aegypti and Culex pipiens complex) in relation to disease epidemics for the current and future climate scenarios. A simulation model for mosquito vector population dynamics was developed based on time-varying distributed delays (TVDD) and multi-way functional response equations implemented in C++ programming language. These equations were implemented to simulate mosquito vectors and hosts developmental stages and also to establish interactions between stages and phases of mosquito vectors in relation to host for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Mark-up Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. A total of 1823 mosquitoes were collected, of which 87.11% were Culex pipiens complex, 12.40% Aedes aegypti and 0.49% Anopheles species. About 36.4% of mosquitoes were collected outdoors using Mosquito Magnets baited with Octenol as an attractant followed by indoor trapping using unbaited CDC light traps (29.60%). Three-hour mosquito collections showed differing patterns in activity, most Ae. aegypti species were collected primarily during the first and last quarters of the day. Cx pipiens complex was active throughout the night, early evening and early morning then decreased markedly during the daytime. Ecological niche models predicted potential suitable areas with high success rates for both species in the current and future climate scenarios. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and north-western Tanzania with records of previous disease epidemics. Other important predicted risk areas include western Lake Victoria, northern parts of Lake Nyasa, and the Rift Valley region in Kenya. During simulation modelling, floodwater Aedines and Culicine populations fluctuated with temperature and water level over simulation period. Simulated mosquito population showed sudden increase between December 1997 and January 1998, a similar period when RVF outbreak occurred in Ngorongoro district. Results provide insights into mosquito abundances and distribution in the district while emphasizing the possibility of using Mosquito Magnets traps for efficient sampling of day biting mosquitoes. Predicted distributions of vectors provide guidance for selection of sampling areas for RVF vectors during IEP. Simulation model results provide new opportunities for climate-driven RVF epidemic modelling

Ecological factors associated with rift valley fever during inter-epidemic period in Tanzania

PhD ThesisRift Valley Fever (RVF) is climate-related arboviral disease of livestock and humans. Rift Valley Fever epidemics are associated with dynamics of mosquito abundance. Studies during inter-epidemic periods (IEP) where there is very little or no virus activity pose challenges including where and how to effectively sample vectors and when should the next outbreaks are expected. Entomological surveys were conducted on abundance and distribution of potential RVF vectors in Ngorongoro district of northern Tanzania. Mosquito sampling techniques and timing were also compared to effectively trap vectors. Mosquitoes were sampled both outdoor and indoor using the CDC light traps and Mosquito Magnets. Outdoor traps were placed in proximity with breeding sites and under canopy in banana plantations in proximity to animals sleeping areas. After every three hours, inspection was done on each trap to recover any trapped mosquito. Traps were set repeatedly in each area for three consecutive days and nights during the study period. All mosquitoes collected were sorted according to site of collection, type of trap and time of collection. Mosquito species were identified morphologically using specific keys. After morphological identification, mosquitoes were kept on ice during transportation to laboratory. Data from this study was used in ecological niche modelling experiment using maximum entropy (MaxEnt) to predict distributions of vectors (Aedes aegypti and Culex pipiens complex) in relation to disease epidemics for the current and future climate scenarios. A simulation model for mosquito vector population dynamics was developed based on time-varying distributed delays (TVDD) and multi-way functional response equations implemented in C++ programming language. These equations were implemented to simulate mosquito vectors and hosts developmental stages and also to establish interactions between stages and phases of mosquito vectors in relation to host for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Mark-up Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. A total of 1823 mosquitoes were collected, of which 87.11% were Culex pipiens complex, 12.40% Aedes aegypti and 0.49% Anopheles species. About 36.4% of mosquitoes were collected outdoors using Mosquito Magnets baited with Octenol as an attractant followed by indoor trapping using unbaited CDC light traps (29.60%). Three-hour mosquito collections showed differing patterns in activity, most Ae. aegypti species were collected primarily during the first and last quarters of the day. Cx pipiens complex was active throughout the night, early evening and early morning then decreased markedly during the daytime. Ecological niche models predicted potential suitable areas with high success rates for both species in the current and future climate scenarios. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and north-western Tanzania with records of previous disease epidemics. Other important predicted risk areas include western Lake Victoria, northern parts of Lake Nyasa, and the Rift Valley region in Kenya. During simulation modelling, floodwater Aedines and Culicine populations fluctuated with temperature and water level over simulation period. Simulated mosquito population showed sudden increase between December 1997 and January 1998, a similar period when RVF outbreak occurred in Ngorongoro district. Results provide insights into mosquito abundances and distribution in the district while emphasizing the possibility of using Mosquito Magnets traps for efficient sampling of day biting mosquitoes. Predicted distributions of vectors provide guidance for selection of sampling areas for RVF vectors during IEP. Simulation model results provide new opportunities for climate-driven RVF epidemic modelling

Climate change and infectious livestock diseases: The case of Rift Valley fever and tick-borne diseases

Climate change influences the occurrence and transmission of a wide range of livestock diseases through multiple pathways. Diseases caused by pathogens that spent part of their life cycle outside the host (e.g. in vectors or the environment) are more sensitive in this regard, compared to those caused by obligate pathogens. In this chapter, we use two well-studied vector-borne diseases—Rift Valley fever (RVF) and tick-borne diseases (TBDs)—as case studies to describe direct pathways through which climate change influences infectious disease-risk in East and southern Africa. The first case study demonstrates that changes in the distribution and frequency of above-normal precipitation increases the frequency of RVF epidemics. The second case study suggests that an increase in temperature would cause shifts in the spatial distribution of TBDs, with cooler and wetter areas expected to experience heightened risk with climate change. These diseases already cause severe losses in agricultural productivity, food security and socio-economic development wherever they occur, and an increase in their incidence or geographical coverage would intensify these losses. We further illustrate some of the control measures that can be used to manage these diseases and recommend that more research should be done to better understand the impacts of climate change on livestock diseases as well as on the effectiveness of the available intervention measures