Clinical malaria case definition and malaria attributable fraction in the highlands of western Kenya.

BackgroundIn African highland areas where endemicity of malaria varies greatly according to altitude and topography, parasitaemia accompanied by fever may not be sufficient to define an episode of clinical malaria in endemic areas. To evaluate the effectiveness of malaria interventions, age-specific case definitions of clinical malaria needs to be determined. Cases of clinical malaria through active case surveillance were quantified in a highland area in Kenya and defined clinical malaria for different age groups.MethodsA cohort of over 1,800 participants from all age groups was selected randomly from over 350 houses in 10 villages stratified by topography and followed for two-and-a-half years. Participants were visited every two weeks and screened for clinical malaria, defined as an individual with malaria-related symptoms (fever [axillary temperature≥37.5°C], chills, severe malaise, headache or vomiting) at the time of examination or 1-2 days prior to the examination in the presence of a Plasmodium falciparum positive blood smear. Individuals in the same cohort were screened for asymptomatic malaria infection during the low and high malaria transmission seasons. Parasite densities and temperature were used to define clinical malaria by age in the population. The proportion of fevers attributable to malaria was calculated using logistic regression models.ResultsIncidence of clinical malaria was highest in valley bottom population (5.0% cases per 1,000 population per year) compared to mid-hill (2.2% cases per 1,000 population per year) and up-hill (1.1% cases per 1,000 population per year) populations. The optimum cut-off parasite densities through the determination of the sensitivity and specificity showed that in children less than five years of age, 500 parasites per μl of blood could be used to define the malaria attributable fever cases for this age group. In children between the ages of 5-14, a parasite density of 1,000 parasites per μl of blood could be used to define the malaria attributable fever cases. For individuals older than 14 years, the cut-off parasite density was 3,000 parasites per μl of blood.ConclusionClinical malaria case definitions are affected by age and endemicity, which needs to be taken into consideration during evaluation of interventions

Surveillance of malaria vector population density and biting behaviour in western Kenya

BACKGROUND: Malaria is a great public health burden and Africa suffers the largest share of malaria-attributed deaths. Despite control efforts targeting indoor malaria transmission, such as insecticide-treated bed nets (ITNs) and deployment of indoor residual spraying, transmission of the parasite in western Kenya is still maintained. This study was carried out to determine the impact of ITNs on indoor vector densities and biting behaviour in western Kenya. METHODS: Indoor collection of adult mosquitoes was done monthly in six study sites in western Kenya using pyrethrum spray collections from 2012 to 2014. The rotator trap collections were done in July–August in 2013 and May–June in 2014. Mosquitoes were collected every 2 h between 18.00 and 08.00 h. Human behaviour study was conducted via questionnaire surveys. Species within Anopheles gambiae complex was differentiated by PCR and sporozoite infectivity was determined by ELISA. Species distribution was determined and bed net coverage in the study sites was recorded. RESULTS: During the study a total of 5,469 mosquito vectors were collected from both PSC and Rotator traps comprising 3,181 (58.2%) Anopheles gambiae and 2,288 (41.8%) Anopheles funestus. Compared to all the study sites, Rae had the highest density of An. gambiae with a mean of 1.2 (P < 0.001) while Kombewa had the highest density of An. funestus with a mean of 1.08 (P < 0.001). Marani had the lowest density of vectors with 0.06 An. gambiae and 0.17 An. funestus (P < 0.001). Among the 700 PCR confirmed An. gambiaes.l. individuals, An. gambiaes.s. accounted for 49% and An. arabiensis 51%. Over 50% of the study population stayed outdoors between 18.00 and 20.00 and 06.00 and 08.00 which was the time when highest densities of blood fed vectors were collected. Anopheles gambies.s. was the main malaria parasite vector in the highland sites and An. arabiensis in the lowland sites. Bed net ownership in 2012 averaged 87% across the study sites. CONCLUSIONS: This study suggests that mass distribution of ITNs has had a significant impact on vector densities, species distribution and sporozoite rate. However, shift of biting time poses significant threats to the current malaria vector control strategies which heavily rely on indoor controls

Epidemiological risk factors for clinical malaria infection in the highlands of Western Kenya.

BackgroundUnderstanding the complex heterogeneity of risk factors that can contribute to an increased risk of malaria at the individual and household level will enable more effective use of control measures. The objective of this study was to understand individual and household factors that influence clinical malaria infection among individuals in the highlands of Western Kenya.MethodsThis was a matched case-control study undertaken in the Western Kenya highlands. Clinical malaria cases were recruited from health facilities and matched to asymptomatic individuals from the community who served as controls. Each participant was screened for malaria using microscopy. Follow-up surveys were conducted with individual households to collect socio-economic data. The houses were also checked using pyrethrum spray catches to collect mosquitoes.ResultsA total of 302 malaria cases were matched to 604 controls during the surveillance period. Mosquito densities were similar in the houses of both groups. A greater percentage of people in the control group (64.6%) used insecticide-treated bed nets (ITNs) compared to the families of malaria cases (48.3%). Use of ITNs was associated with lower level of clinical malaria episodes (odds ratio 0.51; 95% CI 0.39-0.68; P &lt; 0.0001). Low income was the most important factor associated with higher malaria infections (adj. OR 4.70). Use of malaria prophylaxis was the most important factor associated with less malaria infections (adj OR 0.36). Mother's (not fathers) employment status (adj OR 0.48) and education level (adj OR 0.54) was important malaria risk factor. Houses with open eaves was an important malaria risk factor (adj OR 1.72).ConclusionThe identification of risk factors for clinical malaria infection provides information on the local malaria epidemiology and has the potential to lead to a more effective and targeted use of malaria control measures. These risk factors could be used to assess why some individuals acquire clinical malaria whilst others do not and to inform how intervention could be scaled at the local level

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

Clinical malaria case definition and malaria attributable fraction in the highlands of western Kenya

BACKGROUND: In African highland areas where endemicity of malaria varies greatly according to altitude and topography, parasitaemia accompanied by fever may not be sufficient to define an episode of clinical malaria in endemic areas. To evaluate the effectiveness of malaria interventions, age-specific case definitions of clinical malaria needs to be determined. Cases of clinical malaria through active case surveillance were quantified in a highland area in Kenya and defined clinical malaria for different age groups. METHODS: A cohort of over 1,800 participants from all age groups was selected randomly from over 350 houses in 10 villages stratified by topography and followed for two-and-a-half years. Participants were visited every two weeks and screened for clinical malaria, defined as an individual with malaria-related symptoms (fever [axillary temperature ≥ 37.5°C], chills, severe malaise, headache or vomiting) at the time of examination or 1–2 days prior to the examination in the presence of a Plasmodium falciparum positive blood smear. Individuals in the same cohort were screened for asymptomatic malaria infection during the low and high malaria transmission seasons. Parasite densities and temperature were used to define clinical malaria by age in the population. The proportion of fevers attributable to malaria was calculated using logistic regression models. RESULTS: Incidence of clinical malaria was highest in valley bottom population (5.0% cases per 1,000 population per year) compared to mid-hill (2.2% cases per 1,000 population per year) and up-hill (1.1% cases per 1,000 population per year) populations. The optimum cut-off parasite densities through the determination of the sensitivity and specificity showed that in children less than five years of age, 500 parasites per μl of blood could be used to define the malaria attributable fever cases for this age group. In children between the ages of 5–14, a parasite density of 1,000 parasites per μl of blood could be used to define the malaria attributable fever cases. For individuals older than 14 years, the cut-off parasite density was 3,000 parasites per μl of blood. CONCLUSION: Clinical malaria case definitions are affected by age and endemicity, which needs to be taken into consideration during evaluation of interventions

Warmer temperatures reduce the vectorial capacity of malaria mosquitoes

The development rate of parasites and pathogens within vectors typically increases with temperature. Accordingly, transmission intensity is generally assumed to be higher under warmer conditions. However, development is only one component of parasite/pathogen life history and there has been little research exploring the temperature sensitivity of other traits that contribute to transmission intensity. Here, using a rodent malaria, we show that vector competence (the maximum proportion of infectious mosquitoes, which implicitly includes parasite survival across the incubation period) tails off at higher temperatures, even though parasite development rate increases. We also show that the standard measure of the parasite incubation period (i.e. time until the first mosquitoes within a cohort become infectious following an infected blood-meal) is incomplete because parasite development follows a cumulative distribution, which itself varies with temperature. Including these effects in a simple model dramatically alters estimates of transmission intensity and reduces the optimum temperature for transmission. These results highlight the need to understand the interactive effects of environmental temperature on multiple host-disease life-history traits and challenge the assumptions of many current disease models that ignore this complexity

Insecticidal decay effects of long-lasting insecticide nets and indoor residual spraying on Anopheles gambiae and Anopheles arabiensis in Western Kenya

BackgroundIndoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) are the first-line tools for malaria prevention and control in Africa. Vector resistance to insecticides has been extensively studied, however the insecticidal effects of the nets and sprayed walls on pyrethroid resistant mosquitoes has not been studied thoroughly. We evaluated the bioefficacy of LLINs of different ages and lambda-cyhalothrin (ICON 10cs) on the sprayed mud walls for a period of time on malaria vector survivorship.MethodsWHO tube bioassay was performed using diagnostic doses of lambda-cyhalothrin (0.05%), permethrin (0.75%) and deltamethrin (0.05%). Cone bioassays were conducted on netting materials from 0 to 3 years old long-lasting insecticide-impregnated nets. Wall bioassays were performed monthly on mud slabs sprayed with lambdacyhalothrin over a period of seven months. All bioassays used An. gambiae mosquitoes collected from the field and the laboratory susceptible reference Kisumu strain. Concentration of the insecticides on the netting materials was examined using the gas chromatography method. Mosquitoes were identified to species level using PCR and genotyped for the kdr gene mutation frequencies.ResultsWHO bioassays results showed that populations from five sites were highly resistant to the pyrethroids (mortalities ranged from 52.5 to 75.3%), and two sites were moderately resistant to these insecticides (80.4 - 87.2%). Homozygote kdr mutations of L1014S ranged from 73 to 88% in An. gambiae s.s. dominant populations whereas L1014S mutation frequencies were relatively low (7-31%) in An. arabiensis dominant populations. There was a significant decrease (P &lt; 0.05) in mosquito mortality with time after the spray with both lambda-cyhalothrin (75% mortality after six months) and with the age of LLINs (60% mortality after 24 month). Field collected mosquitoes were able to survive exposure to both IRS and LLINs even with newly sprayed walls (86.6-93.5% mortality) and new LLINs (77.5-85.0% mortality), Wild mosquitoes collected from the field had significantly lower mortality rates to LLINs (59.6-85.0%) than laboratory reared susceptible strain (100%). Insecticide concentration decreased significantly from 0.14 μg/ml in the new nets to 0.077 μg/ml in nets older than 18 months (P &lt; 0.05).ConclusionThis study confirms that insecticide decay and developing levels of resistance have a negative contribution to reduced efficacy of ITN and IRS in western Kenya. These factors contribute to decreased efficacy of pyrethroid insectides in ongoing malaria control programs. In order to mitigate against the impact of insecticide resistance and decay it is important to follow the WHO policy to provide the residents with new LLINs every three years of use while maintaining a high level of LLINs coverage and usage. There is also need for urgent development and deployment of non-pyrethroid based vector control tools