Temporal and micro-spatial heterogeneity in the distribution of Anopheles vectors of malaria along the Kenyan coast

The Impact of Climatic Factors on Temporal Mosquito Distribution and Population Dynamics in an Area Targeted for Sterile Insect Technique Pilot Trials

It is widely accepted that climate affects the mosquito life history traits; however, its precise role in determining mosquito distribution and population dynamics is not fully understood. This study aimed to investigate the influence of various climatic factors on the temporal distribution of Anopheles arabiensis populations in Mamfene, South Africa between 2014 and 2019. Time series analysis, wavelet analysis, cross-correlation analysis, and regression model combined with the autoregressive integrated moving average (ARIMA) model were utilized to assess the relationship between climatic factors and An. arabiensis population density. In total 3826 adult An. arabiensis collected was used for the analysis. ARIMA (0, 1, 2) (0, 0, 1)12 models closely described the trends observed in An. arabiensis population density and distribution. The wavelet coherence and time-lagged correlation analysis showed positive correlations between An. arabiensis population density and temperature (r = 0.537 ), humidity (r = 0.495) and rainfall (r = 0.298) whilst wind showed negative correlations (r = -0.466). The regression model showed that temperature (p = 0.00119), rainfall (p = 0.0436), and humidity (p = 0.0441) as significant predictors for forecasting An. arabiensis abundance. The extended ARIMA model (AIC = 102.08) was a better fit for predicting An. arabiensis abundance compared to the basic model. Anopheles arabiensis still remains the predominant malaria vector in the study area and climate variables were found to have varying effects on the distribution and abundance of An. arabiensis. This necessitates other complementary vector control strategies such as the Sterile Insect Technique (SIT) which involves releasing sterile males into the environment to reduce mosquito populations. This requires timely mosquito and climate information to precisely target releases and enhance the effectiveness of the program, consequently reducing the malaria risk.

Updated Anopheles mosquitos abundance and distribution in north-eastern malaria-free area of Argentina

Malaria is the most important parasitic disease worldwide. In 2019, more than 679,441 cases of malaria were reported in the American region. During this study, Argentina was in malaria pre-elimination autochthonous transmission phase with the aim of being declared as malaria-free country. The aim of this work was to assess the influence of remote sensing spectral indices (NDVI, NDWI) and climatic variables (temperature, relative humidity and precipitation) on the distribution and abundance of Anopheles mosquitoes, in four localities with different degrees of anthropogenic disturbance and with previous malaria cases records located , in a historical malarious area in northeastern of Argentina. Between June 2012 and July 2014, mosquitoes were collected. We collected 535 Anopheles adult mosquitoes. Anopheles strodei s.l. was the most abundant species. The greatest richness, diversity and abundance of species were registered in wild and semi-urban environments. The abundance of Anopheles presented a negative association with relative humidity and mean temperature, but positive with mean maximum temperature. The most important variables determining Anopheles total abundance and distribution were NDWI Index and distance to vegetation. The abundance of An. strodei s.l., was positive associated with water areas whereas the NDVI Index was negatively associated.

Impact of Environmental Modifications on the Ecology, Epidemiology, and Pathogenesis of Plasmodium falciparum and Plasmodium vivax Malaria in East Africa

Food insecurity, recurrent famine, and poverty threaten the health of millions of African residents. Construction of dams and rural irrigation schemes is key to solving these problems. The sub-Saharan Africa International Center of Excellence for Malaria Research addresses major knowledge gaps and challenges in Plasmodium falciparum and Plasmodium vivax malaria control and elimination in malaria-endemic areas of Kenya and Ethiopia where major investments in water resource development are taking place. This article highlights progress of the International Center of Excellence for Malaria Research in malaria vector ecology and behavior, epidemiology, and pathogenesis since its inception in 2017. Studies conducted in four field sites in Kenya and Ethiopia show that dams and irrigation increased the abundance, stability, and productivity of larval habitats, resulting in increased malaria transmission and a greater disease burden. These field studies, together with hydrological and malaria transmission modeling, enhance the ability to predict the impact of water resource development projects on vector larval ecology and malaria risks, thereby facilitating the development of optimal water and environmental management practices in the context of malaria control efforts. Intersectoral collaborations and community engagement are crucial to develop and implement cost-effective malaria control strategies that meet food security needs while controlling malaria burden in local communities.

To spray or target mosquitoes another way: focused entomological intelligence guides the implementation of indoor residual spraying in southern Mozambique

BACKGROUND

To eliminate malaria in southern Mozambique, the National Malaria Control Programme and its partners are scaling up indoor residual spraying (IRS) activities in two provinces, Gaza and Inhambane. An entomological surveillance planning tool (ESPT) was used to answer the programmatic question of whether IRS would be effective in target geographies, given limited information on local vector bionomics.

METHODS

Entomological intelligence was collected in six sentinel sites at the end of the rainy season (April-May 2018) and the beginning of the dry season (June-July 2018). The primary objective was to provide an 'entomological snapshot' by collecting question-based, timely and high-quality data within one single week in each location. Host-seeking behaviour (both indoors and outdoors) was monitored by human-baited tent traps. Indoor resting behaviour was quantified by pyrethrum spray catches and window exit traps.

RESULTS

Five different species or species groups were identified: Anopheles funestus sensu lato (s.l.) (66.0%), Anopheles gambiae s.l. (14.0%), Anopheles pharoensis (1.4%), Anopheles tenebrosus (14.1%) and Anopheles ziemanni (4.5%). Anopheles funestus sensu stricto (s.s.) was the major vector among its sibling species, and 1.9% were positive for Plasmodium falciparum infections. Anopheles arabiensis was the most abundant vector species within the An. gambiae complex, but none tested positive for P. falciparum infections. Some An. tenebrosus were positive for P. falciparum (1.3%). When evaluating behaviours that impact IRS efficacy, i.e. endophily, the known primary vector An. funestus s.s., was found to rest indoors-demonstrating at least part of its population will be impacted by the intervention if insecticides are selected to which this vector is susceptible. However, other vector species, including An. gambiae s.l., An. tenebrosus, An. pharoensis and An. ziemanni, showed exophilic and exophagic behaviours in several of the districts surveilled.

CONCLUSION

The targeted approach to entomological surveillance was successful in collecting question-based entomological intelligence to inform decision-making about the use of IRS in specific districts. Endophilic An. funestus s.s. was documented as being the most prevalent and primary malaria vector suggesting that IRS can reduce malaria transmission, but the presence of other vector species both indoors and outdoors suggests that alternative vector control interventions that target these gaps in protection may increase the impact of vector control in southern Mozambique.

Plasmodium falciparum-Specific Memory B-Cell and Antibody Responses Are Associated With Immunity in Children Living in an Endemic Area of Kenya

Identifying the mechanism of naturally acquired immunity against Plasmodium falciparum malaria could contribute to the design of effective malaria vaccines. Using a recently developed multiplexed FluoroSpot assay, we assessed cross-sectional pre-existing memory B-cells (MBCs) and antibody responses against six well known P. falciparum antigens (MSP-119, MSP-2 (3D7), MSP-2 (FC27), MSP-3, AMA-1 and CSP) and measured their associations with previous infections and time to clinical malaria in the ensuing malaria season in Kenyan children. These children were under active weekly surveillance for malaria as part of a long-term longitudinal malaria immunology cohort study, where they are recruited from birth. After performing Cox regression analysis, we found that children with a breadth of three or more antigen-specific MBC or antibody responses at the baseline had a reduced risk for malaria in the ensuing P. falciparum transmission season. Specifically, MBC responses against AMA-1, MSP-2 (3D7) and MSP-3, as well as antibody responses to MSP-2 (3D7) and MSP-3 were prospectively associated with a reduced risk for malaria. The magnitude or breadth of MBC responses were however not correlated with the cumulative number of malaria episodes since birth. We conclude that increased breadth for merozoite antigen-specific MBC and antibody responses is associated with protection against malaria.

Air filtration as a tool for the reduction of viral aerosols

For testing the effectiveness of air purification devices in regard to the reduction of virus-containing aerosols, a test method involving test viruses has been lacking until now. The use of bacteriophages (phiX174 phages) is a method to test the efficiency of air purification devices under experimental conditions. Using air purifiers with a HEPA filter H14, a 4.6-6.1 Log reduction of test viruses can be achieved if bacteriophages are directly aerosolised into the air purifier, which corresponds to a reduction of 99.9974-99.9999%. Due to the complexity and individuality of air flow, an experimental approach was used in which all outside influences were minimised. The experimental setup was practical and chosen to project a scenario of direct transmission by an emitting source to a recipient. The experiments were performed with and without the air purifier at a distance of 0.75 m and 1.5 m each. Using the air purifier at a setting of 1000 m³/h, the concentration of the phiX174 phages in the air could be reduced by 2.86 Log (mean value). Nevertheless, the experiments without the air purifier showed a similar reduction rate of 2.61 Log (mean value) after 35 min. The concentration of phiX174 phages in the air could be additionally reduced up to 1 log step (maximum value) by the use of the air purifier in comparison to the experiments without. Distance was shown to be an important factor for risk reduction.

Entomological and Anthropological Factors Contributing to Persistent Malaria Transmission in Kenya, Ethiopia, and Cameroon

Introduction

In order to improve our understanding of the fundamental limits of core interventions and guide efforts based on prioritization and identification of effective/novel interventions with great potentials to interrupt persistent malaria transmission in the context of high vector control coverage, the drivers of persistent disease transmission were investigated in three eco-epidemiological settings; forested areas in Cameroon, coastal area in Kenya and highland areas in Ethiopia.

Methods

Mosquitoes were sampled in three eco-epidemiological settings using different entomological sampling techniques and analysed for Plasmodium infection status and blood meal origin in blood-fed specimens. Human behavioural surveys were conducted to assess the knowledge and attitude of the population on malaria and preventive measures, their night activities, and sleeping pattern. The parasitological analysis was conducted to determine the prevalence of Plasmodium infection in the population using rapid diagnostic tests.

Results

Despite the diversity in the mosquito fauna, their biting behaviour was found to be closely associated to human behaviour in the three settings. People in Kenya and Ethiopia were found to be more exposed to mosquito bites during the early hours of the evening (18-21h) while it was in the early morning (4-6 am) in Cameroon. Malaria transmission was high in Cameroon compared to Kenya and Ethiopia with over 50% of the infected bites recorded outdoors. The non-users of LLINs were 2.5 to 3 times more likely to be exposed to the risk of acquiring malaria compared to LLINs users. Malaria prevalence was high (42%) in Cameroon, and more than half of the households visited had at least one individual infected with Plasmodium parasites.

Conclusions

The study suggests high outdoor malaria transmission occurring in the three sites with however different determinants driving residual malaria transmission in these areas.

Risk Factors for Household Vector Abundance Using Indoor CDC Light Traps in a High Malaria Transmission Area of Northern Zambia

Malaria transmission is dependent on the density and distribution of mosquito vectors, but drivers of vector abundance have not been adequately studied across a range of transmission settings. To inform intervention strategies for high-burden areas, further investigation is needed to identify predictors of vector abundance. Active household (HH) surveillance was conducted in Nchelenge district, Luapula Province, northern Zambia, a high-transmission setting with limited impact of malaria control. Between April 2012 and July 2017, mosquitoes were collected indoors during HH visits using CDC light traps. Demographic, environmental, and climatological correlates of vector abundance were identified using log-binomial regression models with robust standard errors. The primary malaria vectors in this setting were Anopheles funestus sensu stricto (s.s.) and Anopheles gambiae s.s. Anopheles funestus predominated in both seasons, with a peak in the dry season. Anopheles gambiae peaked at lower numbers in the rainy season. Environmental, climatic, and demographic factors were correlated with HH vector abundance. Higher vector counts were found in rural areas with low population density and among HHs close to roads and small streams. Vector counts were lower with increasing elevation and slope. Anopheles funestus was negatively associated with rainfall at lags of 2-6 weeks, and An. gambiae was positively associated with rainfall at lags of 3-10 weeks. Both vectors had varying relationships with temperature. These results suggest that malaria vector control in Nchelenge district should occur throughout the year, with an increased focus on dry-season transmission and rural areas.

Robust Estimation of Recent Effective Population Size from Number of Independent Origins in Soft Sweeps

Estimating recent effective population size is of great importance in characterizing and predicting the evolution of natural populations. Methods based on nucleotide diversity may underestimate current day effective population sizes due to historical bottlenecks, whereas methods that reconstruct demographic history typically only detect long-term variations. However, soft selective sweeps, which leave a fingerprint of mutational history by recurrent mutations on independent haplotype backgrounds, holds promise of an estimate more representative of recent population history. Here, we present a simple and robust method of estimation based only on knowledge of the number of independent recurrent origins and the current frequency of the beneficial allele in a population sample, independent of the strength of selection and age of the mutation. Using a forward-time theoretical framework, we show the mean number of origins is a function of θ=2Nμ and current allele frequency, through a simple equation, and the distribution is approximately Poisson. This estimate is robust to whether mutants preexisted before selection arose and is equally accurate for diploid populations with incomplete dominance. For fast (e.g., seasonal) demographic changes compared with time scale for fixation of the mutant allele, and for moderate peak-to-trough ratios, we show our constant population size estimate can be used to bound the maximum and minimum population size. Applied to the Vgsc gene of Anopheles gambiae, we estimate an effective population size of roughly 6×107, and including seasonal demographic oscillations, a minimum effective population size >3×107, and a maximum <6×109, suggesting a mean ∼109.

Characterizing the Spatial Determinants and Prevention of Malaria in Kenya

The United Nations' Sustainable Development Goal 3 is to ensure health and well-being for all at all ages with a specific target to end malaria by 2030. Aligned with this goal, the primary objective of this study is to determine the effectiveness of utilizing local spatial variations to uncover the statistical relationships between malaria incidence rate and environmental and behavioral factors across the counties of Kenya. Two data sources are used-Kenya Demographic and Health Surveys of 2000, 2005, 2010, and 2015, and the national Malaria Indicator Survey of 2015. The spatial analysis shows clustering of counties with high malaria incidence rate, or hot spots, in the Lake Victoria region and the east coastal area around Mombasa; there are significant clusters of counties with low incidence rate, or cold spot areas in Nairobi. We apply an analysis technique, geographically weighted regression, that helps to better model how environmental and social determinants are related to malaria incidence rate while accounting for the confounding effects of spatial non-stationarity. Some general patterns persist over the four years of observation. We establish that variables including rainfall, proximity to water, vegetation, and population density, show differential impacts on the incidence of malaria in Kenya. The El-Nino-southern oscillation (ENSO) event in 2015 was significant in driving up malaria in the southern region of Lake Victoria compared with prior time-periods. The applied spatial multivariate clustering analysis indicates the significance of social and behavioral survey responses. This study can help build a better spatially explicit predictive model for malaria in Kenya capturing the role and spatial distribution of environmental, social, behavioral, and other characteristics of the households.

Characterizing local-scale heterogeneity of malaria risk: a case study in Bunkpurugu-Yunyoo district in northern Ghana

BACKGROUND

Bayesian methods have been used to generate country-level and global maps of malaria prevalence. With increasing availability of detailed malaria surveillance data, these methodologies can also be used to identify fine-scale heterogeneity of malaria parasitaemia for operational prevention and control of malaria.

METHODS

In this article, a Bayesian geostatistical model was applied to six malaria parasitaemia surveys conducted during rainy and dry seasons between November 2010 and 2013 to characterize the micro-scale spatial heterogeneity of malaria risk in northern Ghana.

RESULTS

The geostatistical model showed substantial spatial heterogeneity, with malaria parasite prevalence varying between 19 and 90%, and revealing a northeast to southwest gradient of predicted risk. The spatial distribution of prevalence was heavily influenced by two modest urban centres, with a substantially lower prevalence in urban centres compared to rural areas. Although strong seasonal variations were observed, spatial malaria prevalence patterns did not change substantially from year to year. Furthermore, independent surveillance data suggested that the model had a relatively good predictive performance when extrapolated to a neighbouring district.

CONCLUSIONS

This high variability in malaria prevalence is striking, given that this small area (approximately 30 km × 40 km) was purportedly homogeneous based on country-level spatial analysis, suggesting that fine-scale parasitaemia data might be critical to guide district-level programmatic efforts to prevent and control malaria. Extrapolations results suggest that fine-scale parasitaemia data can be useful for spatial predictions in neighbouring unsampled districts and does not have to be collected every year to aid district-level operations, helping to alleviate concerns regarding the cost of fine-scale data collection.

Understanding heterogeneities in mosquito-bite exposure and infection distributions for the elimination of lymphatic filariasis

It is well known that individuals in the same community can be exposed to a highly variable number of mosquito bites. This heterogeneity in bite exposure has consequences for the control of vector-borne diseases because a few people may be contributing significantly to transmission. However, very few studies measure sources of heterogeneity in a way which is relevant to decision-making. We investigate the relationship between two classic measures of heterogeneity, spatial and individual, within the context of lymphatic filariasis, a parasitic mosquito-borne disease. Using infection and mosquito-bite data for five villages in Papua New Guinea, we measure biting characteristics to model what impact bed-nets have had on control of the disease. We combine this analysis with geospatial modelling to understand the spatial relationship between disease indicators and nightly mosquito bites. We found a weak association between biting and infection heterogeneity within villages. The introduction of bed-nets increased biting heterogeneity, but the reduction in mean biting more than compensated for this, by reducing prevalence closer to elimination thresholds. Nightly biting was explained by a spatial heterogeneity model, while parasite load was better explained by an individual heterogeneity model. Spatial and individual heterogeneity are qualitatively different with profoundly different policy implications.

Mapping potential Anopheles gambiae s.l. larval distribution using remotely sensed climatic and environmental variables in Baringo, Kenya

Anopheles gambiae s.l. (Diptera: Culicidae) is responsible for the transmission of the devastating Plasmodium falciparum (Haemosporida: Plasmodiidae) strain of malaria in Africa. This study investigated the relationship between climate and environmental conditions and An. gambiae s.l. larvae abundance and modelled the larval distribution of this species in Baringo County, Kenya. Mosquito larvae were collected using a 350-mL dipper and a pipette once per month from December 2015 to December 2016. A random forest algorithm was used to generate vegetation cover classes. A negative binomial regression was used to model the association between remotely sensed climate (rainfall and temperature) and environmental (vegetation cover, vegetation health, topographic wetness and slope) factors and An. gambiae s.l. for December 2015. Anopheles gambiae s.l. was significantly more frequent in the riverine zone (P < 0.05, r = 0.59) compared with the lowland zone. Rainfall (b = 6.22, P < 0.001), slope (b = - 4.81, P = 0.012) and vegetation health (b = - 5.60, P = 0.038) significantly influenced the distribution of An. gambiae s.l. larvae. High An. gambiae s.l. abundance was associated with cropland and wetland environments. Effective malaria control will require zone-specific interventions such as a focused dry season vector control strategy in the riverine zone.

Explaining variation in adult Anopheles indoor resting abundance: the relative effects of larval habitat proximity and insecticide-treated bed net use

BACKGROUND

Spatial determinants of malaria risk within communities are associated with heterogeneity of exposure to vector mosquitoes. The abundance of adult malaria vectors inside people's houses, where most transmission takes place, should be associated with several factors: proximity of houses to larval habitats, structural characteristics of houses, indoor use of vector control tools containing insecticides, and human behavioural and environmental factors in and near houses. While most previous studies have assessed the association of larval habitat proximity in landscapes with relatively low densities of larval habitats, in this study these relationships were analysed in a region of rural, lowland western Kenya with high larval habitat density.

METHODS

525 houses were sampled for indoor-resting mosquitoes across an 8 by 8 km study area using the pyrethrum spray catch method. A predictive model of larval habitat location in this landscape, previously verified, provided derivations of indices of larval habitat proximity to houses. Using geostatistical regression models, the association of larval habitat proximity, long-lasting insecticidal nets (LLIN) use, house structural characteristics (wall type, roof type), and peridomestic variables (cooking in the house, cattle near the house, number of people sleeping in the house) with mosquito abundance in houses was quantified.

RESULTS

Vector abundance was low (mean, 1.1 adult Anopheles per house). Proximity of larval habitats was a strong predictor of Anopheles abundance. Houses without an LLIN had more female Anopheles gambiae s.s., Anopheles arabiensis and Anopheles funestus than houses where some people used an LLIN (rate ratios, 95% CI 0.87, 0.85-0.89; 0.84, 0.82-0.86; 0.38, 0.37-0.40) and houses where everyone used an LLIN (RR, 95% CI 0.49, 0.48-0.50; 0.39, 0.39-0.40; 0.60, 0.58-0.61). Cooking in the house also reduced Anopheles abundance across all species. The number of people sleeping in the house, presence of cattle near the house, and house structure modulated Anopheles abundance, but the effect varied with Anopheles species and sex.

CONCLUSIONS

Variation in the abundance of indoor-resting Anopheles in rural houses of western Kenya varies with clearly identifiable factors. Results suggest that LLIN use continues to function in reducing vector abundance, and that larval source management in this region could lead to further reductions in malaria risk by reducing the amount of an obligatory resource for mosquitoes near people's homes.

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya

Background

Malaria is an important cause of morbidity and mortality in malaria endemic countries. The malaria mosquito vectors depend on environmental conditions, such as temperature and rainfall, for reproduction and survival. To investigate the potential for weather driven early warning systems to prevent disease occurrence, the disease relationship to weather conditions need to be carefully investigated. Where meteorological observations are scarce, satellite derived products provide new opportunities to study the disease patterns depending on remotely sensed variables. In this study, we explored the lagged association of Normalized Difference Vegetation Index (NVDI), day Land Surface Temperature (LST) and precipitation on malaria mortality in three areas in Western Kenya.

Methodology and Findings

The lagged effect of each environmental variable on weekly malaria mortality was modeled using a Distributed Lag Non Linear Modeling approach. For each variable we constructed a natural spline basis with 3 degrees of freedom for both the lag dimension and the variable. Lag periods up to 12 weeks were considered. The effect of day LST varied between the areas with longer lags. In all the three areas, malaria mortality was associated with precipitation. The risk increased with increasing weekly total precipitation above 20 mm and peaking at 80 mm. The NDVI threshold for increased mortality risk was between 0.3 and 0.4 at shorter lags.

Conclusion

This study identified lag patterns and association of remote- sensing environmental factors and malaria mortality in three malaria endemic regions in Western Kenya. Our results show that rainfall has the most consistent predictive pattern to malaria transmission in the endemic study area. Results highlight a potential for development of locally based early warning forecasts that could potentially reduce the disease burden by enabling timely control actions.

Modelling the relative abundance of the primary African vectors of malaria before and after the implementation of indoor, insecticide-based vector control

Background

Malaria remains a heavy burden across sub-Saharan Africa where transmission is maintained by some of the world’s most efficient vectors. Indoor insecticide-based control measures have significantly reduced transmission, yet elimination remains a distant target. Knowing the relative abundance of the primary vector species can provide transmission models with much needed information to guide targeted control measures. Moreover, understanding how existing interventions are impacting on these relative abundances highlights where alternative control (e.g., larval source management) is needed.

Methods

Using the habitat suitability probabilities generated by predictive species distribution models combined with data collated from the literature, a multinomial generalized additive model was applied to produce relative abundance estimates for Anopheles arabiensis, Anopheles funestus and Anopheles gambiae/Anopheles coluzzii. Using pre- and post-intervention abundance data, estimates of the effect of indoor insecticide-based interventions on these relative abundances were made and are illustrated in post-intervention maps.

Results

Conditional effect plots and relative abundance maps illustrate the individual species’ predicted habitat suitability and how they interact when in sympatry. Anopheles arabiensis and An. funestus show an affinity in habitat preference at the expense of An. gambiae/An. coluzzii, whereas increasing habitat suitability for An. gambiae/An. coluzzii is conversely less suitable for An. arabiensis but has little effect on An. funestus. Indoor insecticide-based interventions had a negative impact on the relative abundance of An. funestus, and a lesser effect on An. arabiensis. Indoor residual spraying had the greatest impact on the relative abundance of An. funestus, and a lesser effect on An. gambiae/An. coluzzii. Insecticide-treated bed nets reduced the relative abundance of both species equally. These results do not indicate changes in the absolute abundance of these species, which may be reduced for all species overall.

Conclusions

The maps presented here highlight the interactions between the primary vector species in sub-Saharan Africa and demonstrate that An. funestus is more susceptible to certain indoor-based insecticide interventions than An. gambiae/An. coluzzii, which in turn, is more susceptible than An. arabiensis. This may provide An. arabiensis with a competitive advantage where it is found in sympatry with other more endophilic vectors, and potentially increase the need for outdoor-based vector interventions to deal with any residual transmission barring the way to malaria elimination.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1187-8) contains supplementary material, which is available to authorized users.

A review of malaria transmission dynamics in forest ecosystems

Malaria continues to be a major health problem in more than 100 endemic countries located primarily in tropical and sub-tropical regions around the world. Malaria transmission is a dynamic process and involves many interlinked factors, from uncontrollable natural environmental conditions to man-made disturbances to nature. Almost half of the population at risk of malaria lives in forest areas. Forests are hot beds of malaria transmission as they provide conditions such as vegetation cover, temperature, rainfall and humidity conditions that are conducive to distribution and survival of malaria vectors. Forests often lack infrastructure and harbor tribes with distinct genetic traits, socio-cultural beliefs and practices that greatly influence malaria transmission dynamics. Here we summarize the various topographical, entomological, parasitological, human ecological and socio-economic factors, which are crucial and shape malaria transmission in forested areas. An in-depth understanding and synthesis of the intricate relationship of these parameters in achieving better malaria control in various types of forest ecosystems is emphasized.

The role of vector control in stopping the transmission of malaria: threats and opportunities

Malaria control, and that of other insect borne diseases such as dengue, is heavily dependent on our ability to control the mosquito populations that transmit these diseases. The major push over the last decade to reduce the global burden of malaria has been driven by the distribution of pyrethroid insecticide-treated bednets and an increase in coverage of indoor residual spraying (IRS). This has reduced malaria deaths by a third. Progress towards the goal of reducing this further is threatened by lack of funding and the selection of drug and insecticide resistance. When malaria control was initially scaled up, there was little pyrethroid resistance in the major vectors, today there is no country in Africa where the vectors remain fully susceptible to pyrethroids. The first pyrethroid resistance mechanisms to be selected produced low-level resistance which had little or no operational significance. More recently, metabolically based resistance has been selected, primarily in West Africa, which in some mosquito populations produces more than 1000-fold resistance. As this spreads the effectiveness of pyrethroid-based bednets and IRS will be compromised. New public health insecticides are not readily available. The pipeline of agrochemical insecticides that can be re-purposed for public health dried up 30 years ago when the target product profile for agricultural insecticides shifted from broad spectrum, stable, contact-acting insecticides to narrow spectrum stomach poisons that could be delivered through the plant. A public–private partnership, the Innovative Vector Control Consortium, was established in 2005 to stimulate the development of new public health pesticides. Nine potential new classes of chemistry are in the pipeline, with the intention of developing three into new insecticides. While this has been successfully achieved, it will still take 6–9 years for new insecticides to reach the market. Careful management of the resistance situation in the interim will be needed if current gains in malaria control are not to be reversed.

Larvicidal effect of disinfectant soap on Anopheles gambiae s.s (Diptera: Culicidae) in laboratory and semifield environs

BACKGROUND

Mosquito larval control using chemicals and biological agents is of paramount importance in vector population and disease incidence reduction. A commercial synthetic disinfectant soap was evaluated against larvae of Anopheles gambiae s.s. in both laboratory and semi field conditions.

METHOD

Five concentrations of commercial synthetic disinfectant soap (0.0001, 0.001, 0.01, 0.1 and 1%) were prepared and evaluated against third instar larvae in laboratory and semi field environments. Mortality was scored at 12, 24, 48, and 72 hrs. Each dosage had 6 replicates, having twenty 3rd instar larvae of An.gambiae s.s.

RESULTS

In the laboratory phase, all dosages had significantly higher larval mortalities than in controls, while in semi field conditions, the dosages of 0.0001, 0.001 and 0.01% had lower mortalities than laboratory trials. In the comparison between semi field and laboratory trials, only 0.1 and 1% dosage had significant difference with more mortality in semifield conditions. Proportions of larvae that died during mortality monitoring intervals in laboratory and semi field had significant differences only at 12 hrs and 72 hrs.

CONCLUSION

The findings of this study have demonstrated that the mortality of larvae caused by commercial synthetic disinfectant soap is worth further studies in open water bodies. More studies are necessary to find out the effect of sunlight on the chemistry of the synthetic disinfectant and other variables in small scale full field trials.