Modeling the Cost Effectiveness of Malaria Control Interventions in the Highlands of Western Kenya

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 control program managers in the study area in adding new or changing implementation of current interventions.     

A Preliminary Continental Risk Map for Malaria Mortality among African Children

Approaches to global public health are increasingly driven by an understanding of regional patterns of disease-specific mortality and disability. Current estimates of disease risks associated with Plasmodium falciparum in sub-Saharan Africa remain poorly defined. Through the integration of high-resolution population and climate probability models of P. falciparum transmission, geographical information systems have been used to define the spatial limits of populations exposed to the risk of infection in Africa. These estimates were combined with a range of annual malaria-specific mortality rates, derived from a variety of epidemiological approaches, among children aged 0–4 years. The best estimates of malaria-attributable mortality using this approach ranged between 0.43 million and 0.68 million deaths per annum among an exposed population of ∼66 million children in 1990. Despite the limitations of modelled transmission and population distributions, these empirical approaches to probabilities of infection risk and epidemiological data on mortality provide a novel approach to present and projected burdens of malaria mortality, as discussed here by Bob Snow, Marlies Craig, Uwe Deichmann and Dave le Sueur.     

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

Background

After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions.

Methods

We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi.

Results

Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk.

Conclusions

The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.     

Conservation Efforts May Increase Malaria Burden in the Brazilian Amazon

Background

Large-scale forest conservation projects are underway in the Brazilian Amazon but little is known regarding their public health impact. Current literature emphasizes how land clearing increases malaria incidence, leading to the conclusion that forest conservation decreases malaria burden. Yet, there is also evidence that proximity to forest fringes increases malaria incidence, which implies the opposite relationship between forest conservation and malaria. We compare the effect of these environmental factors on malaria and explore its implications.

Methods and Findings

Using a large malaria dataset (∼1,300,000 positive malaria tests collected over ∼4.5 million km²), satellite imagery, permutation tests, and hierarchical Bayesian regressions, we show that greater forest cover (as a proxy for proximity to forest fringes) tends to be associated with higher malaria incidence, and that forest cover effect was 25 times greater than the land clearing effect, the often cited culprit of malaria in the region. These findings have important implications for land use/land cover (LULC) policies in the region. We find that cities close to protected areas (PA’s) tend to have higher malaria incidence than cities far from PA’s. Using future LULC scenarios, we show that avoiding 10% of deforestation through better governance might result in an average 2-fold increase in malaria incidence by 2050 in urban health posts.

Conclusions

Our results suggest that cost analysis of reduced carbon emissions from conservation efforts in the region should account for increased malaria morbidity, and that conservation initiatives should consider adopting malaria mitigation strategies. Coordinated actions from disparate science fields, government ministries, and global initiatives (e.g., Reduced Emissions from Deforestation and Degradation; Millenium Development Goals; Roll Back Malaria; and Global Fund to Fight AIDS, Tuberculosis and Malaria), will be required to decrease malaria toll in the region while preserving these important ecosystems.     

Case Based Measles Surveillance in Pune: Evidence to Guide Current and Future Measles Control and Elimination Efforts in India

Background

According to WHO estimates, 35% of global measles deaths in 2011 occurred in India. In 2013, India committed to a goal of measles elimination by 2020. Laboratory supported case based measles surveillance is an essential component of measles elimination strategies. Results from a case-based measles surveillance system in Pune district (November 2009 through December 2011) are reported here with wider implications for measles elimination efforts in India.

Methods

Standard protocols were followed for case identification, investigation and classification. Suspected measles cases were confirmed through serology (IgM) or epidemiological linkage or clinical presentation. Data regarding age, sex, vaccination status were collected and annualized incidence rates for measles and rubella cases calculated.

Results

Of the 1011 suspected measles cases reported to the surveillance system, 76% were confirmed measles, 6% were confirmed rubella, and 17% were non-measles, non-rubella cases. Of the confirmed measles cases, 95% were less than 15 years of age. Annual measles incidence rate was more than 250 per million persons and nearly half were associated with outbreaks. Thirty-nine per cent of the confirmed measles cases were vaccinated with one dose of measles vaccine (MCV1).

Conclusion

Surveillance demonstrated high measles incidence and frequent outbreaks in Pune where MCV1 coverage in infants was above 90%. Results indicate that even high coverage with a single dose of measles vaccine was insufficient to provide population protection and prevent measles outbreaks. An effective measles and rubella surveillance system provides essential information to plan, implement and evaluate measles immunization strategies and monitor progress towards measles elimination.     

Inversion Monophyly in African Anopheline Malaria Vectors

The African Anopheles gambiae complex of six sibling species has many polymorphic and fixed paracentric inversions detectable in polytene chromosomes. These have been used to infer phylogenetic relationships as classically done with Drosophila. Two species, A. gambiae and A. merus, were thought to be sister taxa based on a shared X inversion designated X(ag). Recent DNA data have conflicted with this phylogenetic inference as they have supported a sister taxa relationship of A. gambiae and A. arabiensis. A possible explanation is that the X(ag) is not monophyletic. Here we present data from a gene (soluble guanylate cyclase) within the X(ag) that strongly supports the monophyly of the X(ag). We conjecture that introgression may be occurring between the widely sympatric species A. gambiae and A. arabiensis and that the previous DNA phylogenies have been detecting the introgression. Evidently, introgression is not uniform across the genome, and species-specific regions, like the X-chromosome inversions, do not introgress probably due to selective elimination in hybrids and backcrosses.     

A New Malaria Agent in African Hominids

Plasmodium falciparum is the major human malaria agent responsible for 200 to 300 million infections and one to three million deaths annually, mainly among African infants. The origin and evolution of this pathogen within the human lineage is still unresolved. A single species, P. reichenowi, which infects chimpanzees, is known to be a close sister lineage of P. falciparum. Here we report the discovery of a new Plasmodium species infecting Hominids. This new species has been isolated in two chimpanzees (Pan troglodytes) kept as pets by villagers in Gabon (Africa). Analysis of its complete mitochondrial genome (5529 nucleotides including Cyt b, Cox I and Cox III genes) reveals an older divergence of this lineage from the clade that includes P. falciparum and P. reichenowi (∼21±9 Myrs ago using Bayesian methods and considering that the divergence between P. falciparum and P. reichenowi occurred 4 to 7 million years ago as generally considered in the literature). This time frame would be congruent with the radiation of hominoids, suggesting that this Plasmodium lineage might have been present in early hominoids and that they may both have experienced a simultaneous diversification. Investigation of the nuclear genome of this new species will further the understanding of the genetic adaptations of P. falciparum to humans. The risk of transfer and emergence of this new species in humans must be now seriously considered given that it was found in two chimpanzees living in contact with humans and its close relatedness to the most virulent agent of malaria.     

The Role of Climate Variability in the Spread of Malaria in Bangladeshi Highlands

Background

Malaria is a major public health problem in Bangladesh, frequently occurring as epidemics since the 1990s. Many factors affect increases in malaria cases, including changes in land use, drug resistance, malaria control programs, socioeconomic issues, and climatic factors. No study has examined the relationship between malaria epidemics and climatic factors in Bangladesh. Here, we investigate the relationship between climatic parameters [rainfall, temperature, humidity, sea surface temperature (SST), El Niño-Southern Oscillation (ENSO), the normalized difference vegetation index (NDVI)], and malaria cases over the last 20 years in the malaria endemic district of Chittagong Hill Tracts (CHT).

Methods and Principal Findings

Monthly malaria case data from January 1989 to December 2008, monthly rainfall, temperature, humidity sea surface temperature in the Bay of Bengal and ENSO index at the Niño Region 3 (NIÑO3) were used. A generalized linear negative binomial regression model was developed using the number of monthly malaria cases and each of the climatic parameters. After adjusting for potential mutual confounding between climatic factors there was no evidence for any association between the number of malaria cases and temperature, rainfall and humidity. Only a low NDVI was associated with an increase in the number of malaria cases. There was no evidence of an association between malaria cases and SST in the Bay of Bengal and NIÑO3.

Conclusion and Significance

It seems counterintuitive that a low NDVI, an indicator of low vegetation greenness, is associated with increases in malaria cases, since the primary vectors in Bangladesh, such as An. dirus, are associated with forests. This relationship can be explained by the drying up of rivers and streams creating suitable breeding sites for the vector fauna. Bangladesh has very high vector species diversity and vectors suited to these habitats may be responsible for the observed results.     

Integrating Multiple Distribution Models to Guide Conservation Efforts of an Endangered Toad

Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.     

Dynamics of Socioeconomic Risk Factors for Neglected Tropical Diseases and Malaria in an Armed Conflict

Background

Armed conflict and war are among the leading causes of disability and premature death, and there is a growing share of civilians killed or injured during armed conflicts. A major part of the civilian suffering stems from indirect effects or collateral impact such as changing risk profiles for infectious diseases. We focused on rural communities in the western part of Côte d''Ivoire, where fighting took place during the Ivorian civil war in 2002/2003, and assessed the dynamics of socioeconomic risk factors for neglected tropical diseases (NTDs) and malaria.

Methodology

The same standardized and pre-tested questionnaires were administered to the heads of 182 randomly selected households in 25 villages in the region of Man, western Côte d''Ivoire, shortly before and after the 2002/2003 armed conflict.

Principal Findings

There was no difference in crowding as measured by the number of individuals per sleeping room, but the inadequate sanitation infrastructure prior to the conflict further worsened, and the availability and use of protective measures against mosquito bites and accessibility to health care infrastructure deteriorated. Although the direct causal chain between these findings and the conflict are incomplete, partially explained by the very nature of working in conflict areas, the timing and procedures of the survey, other sources and anecdotal evidence point toward a relationship between an increased risk of suffering from NTDs and malaria and armed conflict.

Conclusion

New research is needed to deepen our understanding of the often diffuse and neglected indirect effects of armed conflict and war, which may be worse than the more obvious, direct effects.     

Shading by Napier Grass Reduces Malaria Vector Larvae in Natural Habitats in Western Kenya Highlands

Increased human population in the Western Kenya highlands has led to reclamation of natural swamps resulting in the creation of habitats suitable for the breeding of Anopheles gambiae, the major malaria vector in the region. Here we report on a study to restore the reclaimed swamp and reverse its suitability as a habitat for malaria vectors. Napier grass-shaded and non-shaded water channels in reclaimed sites in Western Kenya highlands were studied for the presence and density of mosquito larvae, mosquito species composition, and daily variation in water temperature. Shading was associated with 75.5% and 88.4% (P < 0.0001) reduction in anopheline larvae densities and 78.1% and 88% (P < 0.0001) reduction in Anopheles gambiae sensu lato (s.l.) densities in two sites, respectively. Shading was associated with a 5.7°C, 5.0°C, and 4.7°C, and 1.6°C, 3.9°C, and 2.8°C (for maximum, minimum, and average temperatures, respectively) reduction (P < 0.0001) in water temperatures in the two locations, respectively. An. gambiae s.l. was the dominant species, constituting 83.2% and 73.1%, and 44.5% and 42.3%, of anophelines in non-shaded and shaded channels, respectively, in the two sites, respectively. An. gambiae sensu stricto (s.s.) constituted the majority (97.4%) of An. gambiae s.l., while the rest (2.6%) comprised of Anopheles arabiensis. Minimum water temperature decreased with increasing grass height (P = 0.0039 and P = 0.0415 for Lunyerere and Emutete sites, respectively). The results demonstrate how simple environmental strategies can have a strong impact on vector densities.     

Risk Factors for Helminth,Malaria, and HIV Infection in Pregnancy in Entebbe,Uganda

Background

Infections during pregnancy may have serious consequences for both mother and baby. Assessment of risk factors for infections informs planning of interventions and analysis of the impact of infections on health outcomes.

Objectives

To describe risk factors for helminths, malaria and HIV in pregnant Ugandan women before intervention in a trial of de-worming in pregnancy.

Methods

The trial recruited 2,507 pregnant women between April 2003 and November 2005. Participants were interviewed and blood and stool samples obtained; location of residence at enrolment was mapped. Demographic, socioeconomic, behavioral and other risk factors were modelled using logistic regression.

Results

There was a high prevalence of helminth, malaria and HIV infection, as previously reported. All helminths and malaria parasitemia were more common in younger women, and education was protective against every infection. Place of birth and/or tribe affected all helminths in a pattern consistent with the geographical distribution of helminth infections in Uganda. Four different geohelminths (hookworm, Trichuris, Ascaris and Trichostrongylus) showed a downwards trend in prevalence during the enrolment period. There was a negative association between hookworm and HIV, and between hookworm and low CD4 count among HIV-positive women. Locally, high prevalence of schistosomiasis and HIV occurred in lakeshore communities.

Conclusions

Interventions for helminths, malaria and HIV need to target young women both in and out of school. Antenatal interventions for malaria and HIV infection must continue to be promoted. Women originating from a high risk area for a helminth infection remain at high risk after migration to a lower-risk area, and vice versa, but overall, geohelminths seem to be becoming less common in this population. High risk populations, such as fishing communities, require directed effort against schistosomiasis and HIV infection.     

Reliability of School Surveys in Estimating Geographic Variation in Malaria Transmission in the Western Kenyan Highlands

Background

School surveys provide an operational approach to assess malaria transmission through parasite prevalence. There is limited evidence on the comparability of prevalence estimates obtained from school and community surveys carried out at the same locality.

Methods

Concurrent school and community cross-sectional surveys were conducted in 46 school/community clusters in the western Kenyan highlands and households of school children were geolocated. Malaria was assessed by rapid diagnostic test (RDT) and combined seroprevalence of antibodies to bloodstage Plasmodium falciparum antigens.

Results

RDT prevalence in school and community populations was 25.7% (95% CI: 24.4-26.8) and 15.5% (95% CI: 14.4-16.7), respectively. Seroprevalence in the school and community populations was 51.9% (95% CI: 50.5-53.3) and 51.5% (95% CI: 49.5-52.9), respectively. RDT prevalence in schools could differentiate between low (<7%, 95% CI: 0-19%) and high (>39%, 95% CI: 25-49%) transmission areas in the community and, after a simple adjustment, were concordant with the community estimates.

Conclusions

Estimates of malaria prevalence from school surveys were consistently higher than those from community surveys and were strongly correlated. School-based estimates can be used as a reliable indicator of malaria transmission intensity in the wider community and may provide a basis for identifying priority areas for malaria control.     

Malaria epidemic early warning and detection in African highlands

Malaria epidemics have long been known to recur in the African highlands. Efforts to develop systems of early warning and detection for epidemics are outlined here with special emphasis on the Highland Malaria Project (HIMAL). This project has been conducting research on the operational implementation of a district-based surveillance and epidemic-monitoring system using a network of sentinel sites in four pilot districts of Kenya and Uganda. The potential use of weather monitoring as well as disease surveillance for effective early warning is being investigated.     

Malaria Risk Factors in North West Tanzania: The Effect of Spraying,Nets and Wealth

Malaria prevalence remains high in many African countries despite massive scaling-up of insecticide treated nets (ITN) and indoor residual spraying (IRS). This paper evaluates the protective effect of pyrethroid IRS and ITNs in relation to risk factors for malaria based on a study conducted in North-West Tanzania, where IRS has been conducted since 2007 and universal coverage of ITNs has been carried out recently. In 2011 community-based cross-sectional surveys were conducted in the two main malaria transmission periods that occur after the short and long rainy seasons. These included 5,152 and 4,325 children aged 0.5–14 years, respectively. Data on IRS and ITN coverage, household demographics and socio-economic status were collected using an adapted version of the Malaria Indicator Survey. Children were screened for malaria by rapid diagnostic test. In the second survey, haemoglobin density was measured and filter paper blood spots were collected to determine age-specific sero-prevalence in each community surveyed. Plasmodium falciparum infection prevalence in children 0.5–14 years old was 9.3% (95%CI:5.9–14.5) and 22.8% (95%CI:17.3–29.4) in the two surveys. Risk factors for infection after the short rains included households not being sprayed (OR = 0.39; 95%CI:0.20–0.75); low community net ownership (OR = 0.45; 95%CI:0.21–0.95); and low community SES (least poor vs. poorest tertile: OR = 0.13, 95%CI:0.05–0.34). Risk factors after the long rains included household poverty (per quintile increase: OR = 0.89; 95%CI:0.82–0.97) and community poverty (least poor vs. poorest tertile: OR = 0.26, 95%CI:0.15–0.44); household IRS or high community ITN ownership were not protective. Despite high IRS coverage and equitable LLIN distribution, poverty was an important risk factor for malaria suggesting it could be beneficial to target additional malaria control activities to poor households and communities. High malaria prevalence in some clusters and the limited protection given by pyrethroid IRS and LLINs suggest that it may be necessary to enhance established vector control activities and consider additional interventions.