Identification of malaria transmission and epidemic hotspots in the western Kenya highlands: its application to malaria epidemic prediction

<p>Abstract</p> <p>Background</p> <p>Malaria in the western Kenya highlands is characterized by unstable and high transmission variability which results in epidemics during periods of suitable climatic conditions. The sensitivity of a site to malaria epidemics depends on the level of immunity of the human population. This study examined how terrain in the highlands affects exposure and sensitivity of a site to malaria.</p> <p>Methods</p> <p>The study was conducted in five sites in the western Kenya highlands, two U-shaped valleys (Iguhu, Emutete), two V-shaped valleys (Marani, Fort-Ternan) and one plateau (Shikondi) for 16 months among 6-15 years old children. Exposure to malaria was tested using circum-sporozoite protein (CSP) and merozoite surface protein (MSP) immunochromatographic antibody tests; malaria infections were tested by microscopic examination of thick and thin smears, the children's homes were georeferenced using a global positioning system. Paired t-test was used to compare the mean prevalence rates of the sites, K-function was use to determine if the clustering of malaria infections was significant.</p> <p>Results and Discussion</p> <p>The mean antibody prevalence was 22.6% in Iguhu, 24% in Emutete, 11.5% in Shikondi, 8.3% in Fort-Ternan and 9.3% in Marani. The mean malaria infection prevalence was 23.3% in Iguhu, 21.9% in Emutete, 4.7% in Shikondi, 2.9% in Fort-Ternan and 2.4% in Marani. There was a significant difference in the antibodies and malaria infection prevalence between the two valley systems, and between the two valley systems and the plateau (P < 0.05). There was no significant difference in the antibodies and malaria infection prevalence in the two U-shaped valleys (Iguhu and Emutete) and in the V-shaped valleys (Marani and Fort Ternan) (P > 0.05). There was 8.5- fold and a 2-fold greater parasite and antibody prevalence respectively, in the U-shaped compared to the V-shaped valleys. The plateau antibody and parasite prevalence was similar to that of the V-shaped valleys. There was clustering of malaria antibodies and infections around flat areas in the U-shaped valleys, the infections were randomly distributed in the V-shaped valleys and less clustered at the plateau.</p> <p>Conclusion</p> <p>This study showed that the V-shaped ecosystems have very low malaria prevalence and few individuals with an immune response to two major malaria antigens and they can be considered as epidemic hotspots. These populations are at higher risk of severe forms of malaria during hyper-transmission seasons. The plateau ecosystem has a similar infection and immune response to the V-shaped ecosystems. The U-shaped ecosystems are transmission hotspots.</p

An affordable, quality-assured community-based system for high-resolution entomological surveillance of vector mosquitoes that reflects human malaria infection risk patterns.

ABSTRACT: BACKGROUND: More sensitive and scalable entomological surveillance tools are required to monitor low levels of transmission that are increasingly common across the tropics, particularly where vector control has been successful. A large-scale larviciding programme in urban Dar es Salaam, Tanzania is supported by a community-based (CB) system for trapping adult mosquito densities to monitor programme performance. Methodology An intensive and extensive CB system for routine, longitudinal, programmatic surveillance of malaria vectors and other mosquitoes using the Ifakara Tent Trap (ITT-C) was developed in Urban Dar es Salaam, Tanzania, and validated by comparison with quality assurance (QA) surveys using either ITT-C or human landing catches (HLC), as well as a cross-sectional survey of malaria parasite prevalence in the same housing compounds. RESULTS: Community-based ITT-C had much lower sensitivity per person-night of sampling than HLC (Relative Rate (RR) [95% Confidence Interval (CI)] = 0.079 [0.051, 0.121], P < 0.001 for Anopheles gambiae s.l. and 0.153 [0.137, 0.171], P < 0.001 for Culicines) but only moderately differed from QA surveys with the same trap (0.536 [0.406,0.617], P = 0.001 and 0.747 [0.677,0.824], P < 0.001, for An. gambiae or Culex respectively). Despite the poor sensitivity of the ITT per night of sampling, when CB-ITT was compared with QA-HLC, it proved at least comparably sensitive in absolute terms (171 versus 169 primary vectors caught) and cost-effective (153US$versus 187US$ per An. gambiae caught) because it allowed more spatially extensive and temporally intensive sampling (4284 versus 335 trap nights distributed over 615 versus 240 locations with a mean number of samples per year of 143 versus 141). Despite the very low vectors densities (Annual estimate of about 170 An gambiae s.l bites per person per year), CB-ITT was the only entomological predictor of parasite infection risk (Odds Ratio [95% CI] = 4.43[3.027,7. 454] per An. gambiae or Anopheles funestus caught per night, P =0.0373). Discussion and conclusion CB trapping approaches could be improved with more sensitive traps, but already offer a practical, safe and affordable system for routine programmatic mosquito surveillance and clusters could be distributed across entire countries by adapting the sample submission and quality assurance procedures accordingly

Customised ensemble methodologies for deep learning: boosted residual networks and related approaches

This paper introduces a family of new customised methodologies for ensembles, called Boosted Residual Networks (BRN), which builds a boosted ensemble of Residual Networks by growing the member network at each round of boosting. The proposed approach combines recent developements in Residual Networks - a method for creating very deep networks by including a shortcut layer between different groups of layers - with Deep Incremental Boosting, a methodology to train fast ensembles of networks of increasing depth through the use of boosting. Additionally, we explore a simpler variant of Boosted Residual Networks based on Bagging, called Bagged Residual Networks (BaRN). We then analyse how the recent developments in Ensemble distillation can improve our results.We demonstrate that the synergy of Residual Networks and Deep Incremental Boosting has better potential than simply boosting a Residual Network of fixed structure or using the equivalent Deep Incremental Boosting without the shortcut layers, by permitting the creation of models with better generalisation in significantly less time

Molecular epidemiology of drug-resistant malaria in western Kenya highlands

<p>Abstract</p> <p>Background</p> <p>Since the late 1980s a series of malaria epidemics has occurred in western Kenya highlands. Among the possible factors that may contribute to the highland malaria epidemics, parasite resistance to antimalarials has not been well investigated.</p> <p>Methods</p> <p>Using parasites from highland and lowland areas of western Kenya, we examined key mutations associated with <it>Plasmodium falciparum </it>resistance to sulfadoxine – pyrimethamine and chloroquine, including dihydrofolate reductase (<it>pfdhfr</it>) and dihydropteroate synthetase (<it>pfdhps</it>), chloroquine resistance transporter gene (<it>pfcrt</it>), and multi-drug resistance gene 1 (<it>pfmdr1</it>).</p> <p>Results</p> <p>We found that >70% of samples harbored 76T <it>pfcrt </it>mutations and over 80% of samples harbored quintuple mutations (51I/59R/108N <it>pfdhfr </it>and 437G/540E <it>pfdhps</it>) in both highland and lowland samples. Further, we did not detect significant difference in the frequencies of these mutations between symptomatic and asymptomatic malaria volunteers, and between highland and lowland samples.</p> <p>Conclusion</p> <p>These findings suggest that drug resistance of malaria parasites in the highlands could be contributed by the mutations and their high frequencies as found in the lowland. The results are discussed in terms of the role of drug resistance as a driving force for malaria outbreaks in the highlands.</p

Variations in entomological indices in relation to weather patterns and malaria incidence in East African highlands: implications for epidemic prevention and control

<p>Abstract</p> <p>Background</p> <p>Malaria epidemics remain a significant public health issue in the East African highlands. The aim of this study was to monitor temporal variations in vector densities in relation to changes in meteorological factors and malaria incidence at four highland sites in Kenya and Uganda and to evaluate the implications of these relationships for epidemic prediction and control.</p> <p>Methods</p> <p>Mosquitoes were collected weekly over a period of 47 months while meteorological variables and morbidity data were monitored concurrently. Mixed-effects Poisson regression was used to study the temporal associations of meteorological variables to vector densities and of the latter to incidence rates of <it>Plasmodium falciparum</it>.</p> <p>Results</p> <p><it>Anopheles gambiae </it>s.s. was the predominant vector followed by <it>Anopheles arabiensis</it>. <it>Anopheles funestus </it>was also found in low densities. Vector densities remained low even during periods of malaria outbreaks. Average temperature in previous month and rainfall in previous two months had a quadratic and linear relationship with <it>An. gambiae </it>s.s. density, respectively. A significant statistical interaction was also observed between average temperature and rainfall in the previous month. Increases in densities of this vector in previous two months showed a linear relationship with increased malaria incidence.</p> <p>Conclusion</p> <p>Although epidemics in highlands often appear to follow abnormal weather patterns, interactions between meteorological, entomological and morbidity variables are complex and need to be modelled mathematically to better elucidate the system. This study showed that routine entomological surveillance is not feasible for epidemic monitoring or prediction in areas with low endemicity. However, information on unusual increases in temperature and rainfall should be used to initiate rapid vector surveys to assess transmission risk.</p

Spatial targeted vector control in the highlands of Burundi and its impact on malaria transmission

BACKGROUND: Prevention of malaria epidemics is a priority for African countries. The 2000 malaria epidemic in Burundi prompted the government to implement measures for preventing future outbreaks. Case management with artemisinin-based combination therapy and malaria surveillance were nationally improved. A vector control programme was initiated in one of the most affected highland provinces. The focal distribution of malaria vectors in the highlands was the starting point for designing a targeted vector control strategy. The objective of this study was to present the results of this strategy on malaria transmission in an African highland region. METHODS: In Karuzi, in 2002-2005, vector control activities combining indoor residual spraying and long-lasting insecticidal nets were implemented. The interventions were done before the expected malaria transmission period and targeted the valleys between hills, with the expectation that this would also protect the populations living at higher altitudes. The impact on the Anopheles population and on malaria transmission was determined by nine cross-sectional surveys carried out at regular intervals throughout the study period. RESULTS: Anopheles gambiae s.l. and Anopheles funestus represented 95% of the collected anopheline species. In the valleys, where the vector control activities were implemented, Anopheles density was reduced by 82% (95% CI: 69-90). Similarly, transmission was decreased by 90% (95% CI: 63%-97%, p = 0.001). In the sprayed valleys, Anopheles density was further reduced by 79.5% (95% CI: 51.7-91.3, p < 0.001) in the houses with nets as compared to houses without them. No significant impact on vector density and malaria transmission was observed in the hill tops. However, the intervention focused on the high risk areas near the valley floor, where 93% of the vectors are found and 90% of the transmission occurs. CONCLUSION: Spatial targeted vector control effectively reduced Anopheles density and transmission in this highland district. Bed nets have an additional effect on Anopheles density though this did not translate in an additional impact on transmission. Though no impact was observed in the hilltops, the programme successfully covered the areas most at risk. Such a targeted strategy could prevent the emergence and spread of an epidemic from these high risk foci

Regulatory Response to Carbon Starvation in Caulobacter crescentus

Bacteria adapt to shifts from rapid to slow growth, and have developed strategies for long-term survival during prolonged starvation and stress conditions. We report the regulatory response of C. crescentus to carbon starvation, based on combined high-throughput proteome and transcriptome analyses. Our results identify cell cycle changes in gene expression in response to carbon starvation that involve the prominent role of the FixK FNR/CAP family transcription factor and the CtrA cell cycle regulator. Notably, the SigT ECF sigma factor mediates the carbon starvation-induced degradation of CtrA, while activating a core set of general starvation-stress genes that respond to carbon starvation, osmotic stress, and exposure to heavy metals. Comparison of the response of swarmer cells and stalked cells to carbon starvation revealed four groups of genes that exhibit different expression profiles. Also, cell pole morphogenesis and initiation of chromosome replication normally occurring at the swarmer-to-stalked cell transition are uncoupled in carbon-starved cells

The Early Stage of Bacterial Genome-Reductive Evolution in the Host

The equine-associated obligate pathogen Burkholderia mallei was developed by reductive evolution involving a substantial portion of the genome from Burkholderia pseudomallei, a free-living opportunistic pathogen. With its short history of divergence (∼3.5 myr), B. mallei provides an excellent resource to study the early steps in bacterial genome reductive evolution in the host. By examining 20 genomes of B. mallei and B. pseudomallei, we found that stepwise massive expansion of IS (insertion sequence) elements ISBma1, ISBma2, and IS407A occurred during the evolution of B. mallei. Each element proliferated through the sites where its target selection preference was met. Then, ISBma1 and ISBma2 contributed to the further spread of IS407A by providing secondary insertion sites. This spread increased genomic deletions and rearrangements, which were predominantly mediated by IS407A. There were also nucleotide-level disruptions in a large number of genes. However, no significant signs of erosion were yet noted in these genes. Intriguingly, all these genomic modifications did not seriously alter the gene expression patterns inherited from B. pseudomallei. This efficient and elaborate genomic transition was enabled largely through the formation of the highly flexible IS-blended genome and the guidance by selective forces in the host. The detailed IS intervention, unveiled for the first time in this study, may represent the key component of a general mechanism for early bacterial evolution in the host

Evaluation of two methods of estimating larval habitat productivity in western Kenya highlands

<p>Abstract</p> <p>Background</p> <p>Malaria vector intervention and control programs require reliable and accurate information about vector abundance and their seasonal distribution. The availability of reliable information on the spatial and temporal productivity of larval vector habitats can improve targeting of larval control interventions and our understanding of local malaria transmission and epidemics. The main objective of this study was to evaluate two methods of estimating larval habitat productivity in the western Kenyan highlands, the aerial sampler and the emergence trap.</p> <p>Methods</p> <p>The study was conducted during the dry and rainy seasons in 2008, 2009 and 2010. Aerial samplers and emergence traps were set up for sixty days in each season in three habitat types: drainage ditches, natural swamps, and abandoned goldmines. Aerial samplers and emergence traps were set up in eleven places in each habitat type. The success of each in estimating habitat productivity was assessed according to method, habitat type, and season. The effect of other factors including algae cover, grass cover, habitat depth and width, and habitat water volume on species productivity was analysed using stepwise logistic regression</p> <p>Results</p> <p>Habitat productivity estimates obtained by the two sampling methods differed significantly for all species except for <it>An</it>. <it>implexus</it>. For for <it>An</it>. <it>gambiae </it>s.l. and <it>An</it>. <it>funestus</it>, aerial samplers performed better, 21.5 and 14.6 folds, than emergence trap respectively, while the emergence trap was shown to be more efficient for culicine species. Seasonality had a significant influence on the productivity of all species monitored. Dry season was most productive season. Overall, drainage ditches had significantly higher productivity in all seasons compared to other habitat types. Algae cover, debris, chlorophyll-a, and habitat depth and size had significant influence with respect to species.</p> <p>Conclusion</p> <p>These findings suggest that the aerial sampler is the better of the two methods for estimating the productivity of <it>An</it>. <it>gambiae </it>s.l. and <it>An</it>. <it>funestus </it>in the western Kenya highlands and possibly other malaria endemic parts of Africa. This method has proven to be a useful tool for monitoring malaria vector populations and for control program design, and provides useful means for determining the most suitable sites for targeted interventions.</p

Global warming and malaria: knowing the horse before hitching the cart

Speculations on the potential impact of climate change on human health frequently focus on malaria. Predictions are common that in the coming decades, tens – even hundreds – of millions more cases will occur in regions where the disease is already present, and that transmission will extend to higher latitudes and altitudes. Such predictions, sometimes supported by simple models, are persuasive because they are intuitive, but they sidestep factors that are key to the transmission and epidemiology of the disease: the ecology and behaviour of both humans and vectors, and the immunity of the human population. A holistic view of the natural history of the disease, in the context of these factors and in the precise setting where it is transmitted, is the only valid starting point for assessing the likely significance of future changes in climate