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Introduction The decision-making process for malaria control and elimination strategies has become more challenging. Interventions need to be targeted at council level to allow for changing malaria epidemiology and an increase in the number of possible interventions. Models of malaria dynamics can support this process by simulating potential impacts of multiple interventions in different settings and determining appropriate packages of interventions for meeting specific expected targets. Methods The OpenMalaria model of malaria dynamics was calibrated for all 184 councils in mainland Tanzania using data from malaria indicator surveys, school parasitaemia surveys, entomological surveillance, and vector control deployment data. The simulations were run for different transmission intensities per region and five interventions, currently or potentially included in the National Malaria Strategic Plan, individually and in combination. The simulated prevalences were fitted to council specific prevalences derived from geostatistical models to obtain council specific predictions of the prevalence and number of cases between 2017 and 2020. The predictions were used to evaluate in silico the feasibility of the national target of reaching a prevalence of below 1% by 2020, and to suggest alternative intervention stratifications for the country. Results The historical prevalence trend was fitted for each council with an agreement of 87% in 2016 (95%CI: 0.84–0.90) and an agreement of 90% for the historical trend (2003–2016) (95%CI: 0.87–0.93) The current national malaria strategy was expected to reduce the malaria prevalence between 2016 and 2020 on average by 23.8% (95% CI: 19.7%-27.9%) if current case management levels were maintained, and by 52.1% (95% CI: 48.8%-55.3%) if the case management were improved. Insecticide treated nets and case management were the most cost-effective interventions, expected to reduce the prevalence by 25.0% (95% CI: 19.7%-30.2) and to avert 37 millio

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The parasites belonging to the genus Plasmodium are the cause of the second deadliest infectious disease in the world, malaria. Sub Saharan Africa harbours more than 90% of malaria attributable mortality and morbidity, and most deaths occur in children under 18 years old. Malaria is transmitted to humans by a bite of a Plasmodium infected arthropod vector from the genus Anopheles. Halfway the 20th century malaria was successfully eliminated from most developed countries, nonetheless in the third world effective control remains a laborious challenge. Intensive efforts undertaken to control and eventually eradicate malaria during the past decade have led to substantial reductions in morbidity and mortality. Conversely, scientists became increasingly aware that with the current preventative and curative tools against malaria successful eradication seems unlikely. Not only do current tools not suffice to attain that goal, their efficacy to control malaria as it is, maybe severely threatened. Proper treatment and diagnosis are becoming increasingly less effective because of the adaptive nature of the parasite. Parasites get resistance against drugs and carriers are more often found to have subclinical infections. Likewise prevention of malaria, by vector control, becomes less effective. Malaria vectors become resistant to insecticides and transmission patterns are shifting away from where preventive measures are functional: outside and during the day. It this gap where the SolarMal project experimented with a novel malaria vector control tool, complimentary to existing malaria control methods: odour-baited mosquito traps that mimic human beings to lure and kill mosquitoes to eventually reduce malaria. The ultimate aim of this thesis was to seek proof of principle of the effect of mass trapping of malaria vectors on malaria and mosquito densities by rolling out over 4000 odour-baited mosquito traps at household level on Rusinga Island, Kenya. Chapter 2 is a study protocol

Background: Large reductions in malaria transmission and mortality have been achieved over the last decade, and this has mainly been attributed to the scale-up of long-lasting insecticidal bed nets and indoor residual spraying with insecticides. Despite these gains considerable residual, spatially heterogeneous, transmission remains. To reduce transmission in these foci, researchers need to consider the local demographical, environmental and social context, and design an appropriate set of interventions. Exploring spatially variable risk factors for malaria can give insight into which human and environmental characteristics play important roles in sustaining malaria transmission. Methods: On Rusinga Island, western Kenya, malaria infection was tested by rapid diagnostic tests during two cross-sectional surveys conducted 3 months apart in 3632 individuals from 790 households. For all households demographic data were collected by means of questionnaires. Environmental variables were derived using Quickbird satellite images. Analyses were performed on 81 project clusters constructed by a traveling salesman algorithm, each containing 50-51 households. A standard linear regression model was fitted containing multiple variables to determine how much of the spatial variation in malaria prevalence could be explained by the demographic and environmental data. Subsequently, a geographically-weighted regression (GWR) was performed assuming non-stationarity of risk factors. Special attention was taken to investigate the effect of residual spatial autocorrelation and local multicollinearity. Results: Combining the data from both surveys, overall malaria prevalence was 24 %. Scan statistics revealed two clusters which had significantly elevated numbers of malaria cases compared to the background prevalence across the rest of the study area. A multivariable linear model including environmental and household factors revealed that higher socioeconomic status, outdoor occupation and

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Contains fulltext : 138950.pdf (publisher's version ) (Open Access), INTRODUCTION: Tools that allow for in silico optimization of available malaria control strategies can assist the decision-making process for prioritizing interventions. The OpenMalaria stochastic simulation modeling platform can be applied to simulate the impact of interventions singly and in combination as implemented in Rachuonyo South District, western Kenya, to support this goal. METHODS: Combinations of malaria interventions were simulated using a previously-published, validated model of malaria epidemiology and control in the study area. An economic model of the costs of case management and malaria control interventions in Kenya was applied to simulation results and cost-effectiveness of each intervention combination compared to the corresponding simulated outputs of a scenario without interventions. Uncertainty was evaluated by varying health system and intervention delivery parameters. RESULTS: The intervention strategy with the greatest simulated health impact employed long lasting insecticide treated net (LLIN) use by 80% of the population, 90% of households covered by indoor residual spraying (IRS) with deployment starting in April, and intermittent screen and treat (IST) of school children using Artemether lumefantrine (AL) with 80% coverage twice per term. However, the current malaria control strategy in the study area including LLIN use of 56% and IRS coverage of 70% was the most cost effective at reducing disability-adjusted life years (DALYs) over a five year period. CONCLUSIONS: All the simulated intervention combinations can be considered cost effective in the context of available resources for health in Kenya. Increasing coverage of vector control interventions has a larger simulated impact compared to adding IST to the current implementation strategy, suggesting that transmission in the study area is not at a level to warrant replacing vector control to a school-based screen and treat program. These results have the potential to assist malaria co

Background There has recently been a substantial decline in malaria incidence in much of Africa. While the decline can clearly be linked to increasing coverage of mosquito vector control interventions and effective drug treatment in most settings, the ubiquity of reduction raises the possibility that additional ecological and associated evolutionary changes may be reinforcing the effectiveness of current vector control strategies in previously unanticipated ways. Presentation of hypothesis Here it is hypothesized that the increasing coverage of insecticide-treated bed nets and other vector control methods may be driving selection for a shift in mosquito life history that reduces their ability to transmit malaria parasites. Specifically it is hypothesized that by substantially increasing the extrinsic rate of mortality experienced in vector populations, these interventions are creating a fitness incentive for mosquitoes to re-allocate their resources towards greater short-term reproduction at the expense of longer-term survival. As malaria transmission is fundamentally dependent on mosquito survival, a life history shift in this direction would greatly benefit control. Testing the hypothesis At present, direct evaluation of this hypothesis within natural vector populations presents several logistical and methodological challenges. In the meantime, many insights can be gained from research previously conducted on wild Drosophila populations. Long-term selection experiments on these organisms suggest that increasing extrinsic mortality by a magnitude similar to that anticipated from the up-scaling of vector control measures generated an increase in their intrinsic mortality rate. Although this increase was small, a change of similar magnitude in Anopheles vector populations would be predicted to reduce malaria transmission by 80%. Implications of hypothesis The hypothesis presented here provides a reminder that evolutionary processes induced by interventions against di

Background The communities of Namawala and Idete villages in southern Tanzania experienced extremely high malaria transmission in the 1990s. By 2001-03, following high usage rates (75% of all age groups) of untreated bed nets, a 4.2-fold reduction in malaria transmission intensity was achieved. Since 2006, a national-scale programme has promoted the use of longer-lasting insecticide treatment kits (consisting of an insecticide plus binder) co-packaged with all bed nets manufactured in the country. Methods The entomological inoculation rate (EIR) was estimated through monthly surveys in 72 houses randomly selected in each of the two villages. Mosquitoes were caught using CDC light traps placed beside occupied bed nets between January and December 2008 (n = 1,648 trap nights). Sub-samples of mosquitoes were taken from each trap to determine parity status, sporozoite infection and Anopheles gambiae complex sibling species identity. Results Compared with a historical mean EIR of ~1400 infectious bites/person/year (ib/p/y) in 1990-94; the 2008 estimate of 81 ib/p/y represents an 18-fold reduction for an unprotected person without a net. The combined impact of longer-lasting insecticide treatments as well as high bed net coverage was associated with a 4.6-fold reduction in EIR, on top of the impact from the use of untreated nets alone. The scale-up of bed nets and subsequent insecticidal treatment has reduced the density of the anthropophagic, endophagic primary vector species, Anopheles gambiae sensu stricto, by 79%. In contrast, the reduction in density of the zoophagic, exophagic sibling species Anopheles arabiensis was only 38%. Conclusion Insecticide treatment of nets reduced the intensity of malaria transmission in addition to that achieved by the untreated nets alone. Impacts were most pronounced against the highly anthropophagic, endophagic primary vector, leading to a shift in the sibling species composition of the A. gambiae complex