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      Physical condition and maintenance of mosquito bed nets in Kwale County, coastal Kenya

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          Despite the extensive ownership and use of insecticide-treated nets (ITNs) over the last decade, the effective lifespan of these nets, especially their physical integrity, under true operational conditions is not well-understood. Usefulness of nets declines primarily due to physical damage or loss of insecticidal activity.


          A community based cross-sectional survey was used to determine the physical condition and to identify predictors of poor physical condition for bed nets owned by individuals from communities in Kwale County, coastal Kenya. A proportionate hole index (pHI) was used as a standard measure, and the cut-offs for an ‘effective net’ (offer substantial protection against mosquito bites) and ‘ineffective nets’ (offer little or no protection against mosquito bites) were determined (pHI ≤88 (about ≤500 cm 2 of holes surface area) and pHI of >88 (≥500 cm 2 of holes surface area), respectively).


          The vast majority (78%) of the surveyed nets had some holes. The median pHI was 92 (range: 1–2,980). Overall, half of the nets were categorized as ‘effective nets’ or ‘serviceable nets’. Physical deterioration of nets was associated with higher use and washing frequency. Young children and older children were found to use ineffective bed nets significantly more often than infants, while the physical integrity of nets owned by pregnant women was similar to those owned by infants. Estuarine environment inhabitants owned nets with the worst physical condition, while nets owned by the coastal slope inhabitants were in fairly good physical condition. The results suggest that bed nets are optimally utilized when they are new and physically intact. Thereafter, bed net utilization decreases gradually with increasing physical deterioration, with most net owners withdrawing physically damaged nets from routine use.

          This withdrawal commonly happens following 1.5 years of use, making bed net use the most important predictor of physical integrity. On average, the nets were washed twice within six months prior to the survey. Washing frequency was significantly influenced by the bed net colour and bed net age. Lack of knowledge on reasons for net retreatment and the retreatment procedure was evident, while net repair was minimal and did not seem to improve the physical condition of the nets. The “catch-up” bed net distribution strategies are sufficient for ensuring adequate ownership and utilization of ‘effective nets’ in the targeted groups, but bi-annual mass distribution is necessary to provide similar ownership and utilization for the other groups not targeted by “catch-up” strategies.


          Monitoring and maintenance strategies that will deliver locally appropriate education messages on net washing and repair will enhance the effectiveness of malaria control programmes, and further research to assess ineffective nets need is needed.

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          Pyrethroid resistance in African anopheline mosquitoes: what are the implications for malaria control?

          The use of pyrethroid insecticides in malaria vector control has increased dramatically in the past decade through the scale up of insecticide treated net distribution programmes and indoor residual spraying campaigns. Inevitably, the major malaria vectors have developed resistance to these insecticides and the resistance alleles are spreading at an exceptionally rapid rate throughout Africa. Although substantial progress has been made on understanding the causes of pyrethroid resistance, remarkably few studies have focused on the epidemiological impact of resistance on current malaria control activities. As we move into the malaria eradication era, it is vital that the implications of insecticide resistance are understood and strategies to mitigate these effects are implemented. Copyright © 2010 Elsevier Ltd. All rights reserved.
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            Increasing Coverage and Decreasing Inequity in Insecticide-Treated Bed Net Use among Rural Kenyan Children

            Introduction The gulf between levels of childhood mortality in sub-Saharan Africa and access to simple, cost-effective interventions known to significantly reduce mortality is immoral [1]. For over ten years it has been known that insecticide-treated bed nets (ITNs) can reduce childhood mortality by 17% [2]. In 1998 the Roll Back Malaria (RBM) movement was launched with one of its primary objectives to increase ITN coverage among vulnerable groups, such as children and pregnant women, to over 60% [3]. RBM has recently revised this ITN objective to reach 80% coverage by 2010 [4]. This change in target followed the RBM publication of the current status of ITN coverage in Africa as part of its World Malaria Report [5]. Of 34 malaria-endemic countries in Africa providing recent national data, only one (Eritrea) had achieved ITN coverage among children aged less than 5 y of more than 60% [5]. Reasons for this dismal progress has been the subject of much debate [6–9] and largely centre around divergent views on optimal strategies to deliver ITNs to economically and biologically vulnerable groups across Africa. During the early days of RBM, the technical advice to countries provided by World Health Organization (WHO) was to create an “enabling environment” that allowed malaria-endemic countries to embrace multiple approaches to providing ITNs [10]. These approaches included building sustainable private for-profit markets, for example through the NETMARK initiative in nine African countries [11]; creating a not-for-profit commercial sector through social marketing, a model promoted by Population Services International (PSI) operating in 23 African countries [12]; or the less popular at the time option of providing ITNs free of charge through clinics, or as first suggested in 1995, through vaccine campaigns [13]. The best-practice debate has been driven by personal opinion [6,7] or data on temporal changes in ITN coverage associated with single delivery approaches [14–16]. Where data exist they compare information on a single delivery model against a baseline without significant intervention or iterative increases in net coverage associated with a single, nationally adopted approach to delivery. Rarely is it possible to compare incremental coverage associated with different delivery models. Here we present a serial observation of ITN coverage among rural Kenyan communities exposed at different times to the range of delivery models each with legitimate claims to improve ITN access. Our emphasis throughout this study was to examine how ITN access by the poorest sectors of rural communities might best be achieved with each approach. Methods The Kenya ITN Context Prior to the launch of Kenya's National Malaria Strategy in April 2001 [17], access to nets was limited to the private for-profit retail sector and special project-based distributions through research- or nongovernmental organization-led community development initiatives [18]. In 2000 the Kenya Ministry of Health (MoH) developed with partners an ITN strategy paper [19] that attempted to accommodate two competing views on ways to reach the government's target of 60% coverage of populations at risk by 2005. The first approach included ways to ensure that the ITN market is self-sustaining in the absence of long-term donor support by expanding the private sector through social marketing; the second approach, principally favoured by the MoH, was to provide ITNs free of charge to pregnant women and children under the age of 5 y to achieve rapid scale-up. In January 2002 the UK Department for International Development (DFID) awarded PSI-Kenya US$33 million over 5 y to socially market partially subsidised ITN within the existing retail sector. The programme, named PSI Coverage Plus, was the only major operational ITN distribution initiative between 2002 and 2004 and aimed to target urban and rural retail outlets with Supanet ITNs across all malaria-endemic districts in Kenya. A two-tier pricing system of 350 Kenya Shillings (KES) (equivalent to US$4.7) in urban settings versus KES100 (US$1.3) in rural settings was implemented. The programme's aims were to increase community awareness of the value of ITNs thus creating a “net culture”; force existing retail prices down; and increase clients' willingness to pay for nets through a sustainable, unsubsidised commercial market [20]. In June 2004, DFID approved an additional US$19 million to PSI to establish a parallel distribution system of heavily subsidised ITNs to children and pregnant women through Maternal and Child Health (MCH) clinics, recognizing that these vulnerable groups might not be able to access socially marketed commercial sector nets. The programme began in October 2004, and during the first 6 mo Supanet ITNs were bundled with separate Powertab net treatment tablets (for every 6 mo) and distributed to MCH attendees. In May 2005 an additional US$37 million was committed by DFID to PSI to procure and distribute Supanet-branded long-lasting insecticidal nets (LLINs), Olyset and Permanet. These public sector nets were heavily subsidized pretreated nets (KES50; US$0.7) and branded with the MoH logo [20]. In February 2002 the MoH responded to the first call of the Global Fund to Fight AIDS, TB and Malaria (GFATM) for funding applications to secure five million nets and net treatments to provide free of charge to children under the age of 5 y and pregnant women. This application was unsuccessful. During round four of the GFATM awards in April 2004, Kenya's application was successful and US$17 million was approved to procure and distribute 3.4 million LLINs (Olyset and Permanet brands) free of charge to children under the age of 5 y. This represented, at the time, the largest successful award for free distribution of LLINs in Africa. The implementation of the free mass distribution of LLINs was arranged in two phases during 2006. During the first phase, 21 of Kenya's 70 districts were selected for distribution of LLINs from 8 to 12 July 2006 and integrated with the national measles catch-up vaccination campaign. Health facilities and centralised non-health facility posts were identified by the Kenya Expanded Programme on Immunisation and used as delivery points of both measles vaccine and LLINs to each child under the age of 5 y. A second mass distribution of LLINs, not integrated with any other intervention, took place from 25 to 27 September 2006 in 24 additional districts using previous mass vaccine campaign delivery centres as distribution points. Study Area The study was carried out in four districts purposively sampled in collaboration with the MoH to provide detailed longitudinal milestone data on changing access to interventions proposed within the Kenya National Malaria Strategy between 2001 and 2006 [21,22]. The study districts represent the range of dominant malaria epidemiological situations that prevail across Kenya: Kwale on the coast with seasonal high-intensity malaria transmission; Bondo on the shores of Lake Victoria with perennial high-intensity transmission; Greater Kisii district (combining the new districts of Kisii Central and Gucha) with seasonal low transmission conditions of the Western highlands; and Makueni district, a semi-arid area with acutely seasonal low malaria transmission. Between 63% and 71% of households in the rural areas of each of the four districts were living below the poverty line (equivalent to US$1 per day) in 1999, compared to the national average of 54% [23]. The districts were also representative of rural districts in Kenya with respect to net delivery since 2001, with service providers including the full-cost commercial and social marketing retail sector; a research team in parts of Bondo district [24]; nongovernmental organization delivery to selected communities in Greater Kisii (Merlin and World Vision) and Kwale (Plan International and The Aga Khan Foundation); time-limited MoH provision of free nets to pregnant women in 2001 in all districts [25] and to children and pregnant women in Bondo and Gucha districts in 2005 [26]; and subsidized PSI clinic distribution since October 2004 and mass, free distribution in 2006 across all districts. Within each district, rural enumeration area (EA) boundaries were digitized with ARCGIS 9.0 (ESRI, and each polygon attributed to population totals derived from the last national census in 1999 [27]. A sample of 18 rural EA polygons, covering approximately 6,500 people per district, was randomly selected from each district to form the basis of the longitudinal community surveillance. Following community sensitisation, all homesteads within an EA polygon were mapped and heads of homesteads were given the purpose of the longitudinal study and asked whether they wished to participate. All de jure resident homestead members were enumerated, including details of date of birth and sex, and issued a unique identifier for follow-up. The Longitudinal Cohort During December/January of 2004/5, 2005/6, and 2006/7, just after the short rains, a cohort of children under the age of 5 y was established to track, by interviewing mothers or caretakers, the ownership and use of bed nets, including details on the net brand, where and when they were obtained, and whether nets had been treated with an insecticide during the previous 6 mo. Interviewers were instructed to observe the nets and record details of the colour, imprinted logos, and shape of the net to match the net types delivered by different partners in each district at different times. All children resident in 2004 were recruited into the cohort and exited during subsequent census rounds if they had out-migrated, homesteads or guardians subsequently refused participation, they had reached their fifth birthday, or they had died. New children were recruited into the cohort if they had migrated into the homestead between census rounds or were identified through detailed birth histories of all resident women aged 15–49 y as having been born during the interval. New infants who did not survive the interval between census rounds were included in the cohort. In-migrations that out-migrated between the census rounds were not included in the cohort and were regarded as short-term visitors not permanently resident. During the 2005/6 annual census round, representing the reference midpoint of the surveillance period, details were recorded on each homestead relating to key asset indicators, including: homestead head education level and occupation; housing characteristics (type of wall, roof, and floor); source of drinking water; type of sanitation facility; homestead size; and persons per sleeping room (see Table S1). Data Entry and Analysis Data entry and storage were undertaken using Microsoft Access, and analysis was undertaken using STATA version 9.2 (Stata, and ARCGIS 9.0 (ESRI). All information specific to the EA, homestead, and mother or guardian were linked to the relevant child through the use of a primary homestead identifier consistent across all data sets. To account for unequal probabilities of selection of EAs, all results were weighted (weight = 1/probability of selection) and precision of proportions (95% confidence intervals [CIs]) were adjusted for clustering with EA as the primary sampling unit. A χ2 test was performed to compare net use proportions across subgroups within and between survey years. For comparisons of socioeconomic groups within a survey year, the Pearson χ2 statistic, accounting for clustering, was used. This statistic is turned into an F-statistic using the second-order Rao and Scott correction and p-values interpreted the same way as the Pearson χ2 statistic for data without clustering [28,29]. A homestead wealth index was constructed from the asset indicators using principal component analysis. Weights (scoring coefficients) derived from the first principal component were used to construct the wealth index [30]. Weights for each asset indicator from the first principal component were then applied to each homestead record to produce a wealth index. Wealth asset indices were developed separately for each district to allow for innate differences in the meaning of different assets between districts. Each homestead was then assigned to a district-specific wealth quintile. Net ownership by children in the cohort was examined serially and by source according to wealth asset quintiles. Inequity in net coverage over time and by source was analysed using the concentration index, which gives values between −1 and 1, with a value 0 indicating an absence of wealth-related inequality in net use among children [31]. Because net use is a “good” health variable, a positive value of the index indicates net use is concentrated among the wealthy. The concentration curve was plotted to illustrate changes in wealth-related inequality [31]. Ethical Approval Ethical approval was provided by the National Ethical Review Board IRB (Kenya Medical Research Institute SSC number 906). Results A total of 2,761 homesteads were selected across the 72 rural communities located in the four districts in 2004. Three homesteads refused participation in 2004 (0.01%); 11,050 observations of children under the age of 5 y were made across the three survey years in 2004/5, 2005/6, and 2006/7. Over the three years, 155 (1.4%) usually resident children were visiting elsewhere at the time of the annual surveys, 66 (0.6%) children's parents or guardians refused to be interviewed and 133 (1.2%) children died before the census rounds in 2005/6 and 2006/7. In 2004/5 the weighted proportion of children usually using a net, adjusted for clustering, was 13.9%, similar to the proportions of children using a net the night before the survey (Table 1). The small difference between usual use of a net and net use the night before survey was a consistent finding across all surveys (Table 1). We elected to restrict subsequent analysis to net use the night before survey. In 2004/5 the majority of children (65%) who slept under a net were sleeping under nets purchased from the commercial retail sector, only 7% of children slept the night before the survey under nets treated with an insecticide within the last 6 mo, and the proportion ITN use among children living in the poorest quintile homesteads was one-fifth (2.9%) to the proportion of those living in the least poor homesteads (Table 1). Table 1 Net Usage by Children across Four Districts in Three Consecutive Survey Years In December/January 2005/6, 12 mo after the baseline survey, the proportions of children sleeping under a net had increased to 32% where the dominant net source was the heavily subsidized PSI-MCH clinic nets; 58% of children using a net were using nets from this source (Table 1). The proportion of children sleeping under a net treated with an insecticide in the last 6 mo had tripled to over 23% compared to 2004/5 (p < 0.001). Children living in the poorest homesteads had proportionately the largest (six-fold) increase in ITN use over the 12 mo interval, rising from 2.9% in 2004/5 to 17.5% in 2005/6 (p < 0.001); however, children living in the least poor homesteads were still twice as likely to have slept under an ITN the previous night as those in the poorest homesteads (Table 1). These results are reinforced by the concentration indices, which remained positive (net use highest among the wealthier groups) in both rounds of the survey, although the measure of wealth-related inequality, the concentration index, fell from 0.281 in 2004/5 to 0.131 in 2005/6. By December/January 2006/7, the proportion of children sleeping under a net increased to 81%, with the two dominant sources of nets being the free mass campaign (44%) and the PSI-MCH clinics (41%) (Table 1). Within 12 mo of the previous survey, the proportion of children sleeping under an ITN had doubled to 67%; 44% of children were sleeping under an ITN provided during the mass campaign. The largest increase in the proportion of children sleeping under an ITN was among those from homesteads in the poorest quintile, from 17.5% in 2005/6 to 66.3% in 2006/7. There was no statistically significant difference in the proportion of children using an ITN between highest and lowest wealth quintiles in 2006/7 (p = 0.963). The poverty concentration index declined from 0.131 in 2005/6 to 0.000 in 2006/7 (Table 1). The concentration curve indicated, for the first time, the absence of wealth-related inequality in net use (Figure 1) further illustrated by the graph of actual proportions (Figure 2). Figure 1 Degree of Inequality in Children Sleeping under an ITN in 2004/5, 2005/6, and 2006/7 in Homesteads of Different Wealth Status in the Four Districts in Kenya The concentration curve below the line of perfect equality indicates that ITN use is concentrated among higher socioeconomic groups. When the curve is coincident on the line of perfect equality, then there is no wealth-related inequality in ITN use. Figure 2 Proportion of Children Sleeping under an ITN in 2004/5, 2005/6, and 2006/7 in Homesteads of Different Wealth Status in Four Districts in Kenya By the end of September 2006, the three principal net distribution strategies (retail social marketing, heavily subsidized clinic distribution, and free mass distribution) were all operating in parallel, providing an opportunity to examine socioeconomic targeting of each of the delivery mechanisms (Table 2). In 2006/7 2.4% and 24.3% of children from the poorest homesteads slept under a net from the retail sector and the PSI-MCH programme, respectively, compared to 6.4% and 30.8% from the least poor. Conversely, by 2006/7 the highest proportion of children from the poorest homesteads slept under nets from the free mass campaign (most poor/least poor: 36.6%/25.8%). This pattern is further illustrated by the concentration curve (Figure 3), which shows that the free mass campaign is the only delivery channel favouring the poorest children; the PSI-MCH programme was marginally in favour of the least poor, and the commercial sector was the most inequitable in favour of the least poor. Table 2 Variations in Children's Net Use the Night before the 2006/7 Survey by Source across Different Socioeconomic Groups Figure 3 Degree of Inequality in Socioeconomic Targeting by the Three Principal Net Delivery Mechanisms in Four Districts in Kenya by 2006/7 Delivery mechanisms included commercial social marketing, the PSI-MCH programme, and a free mass campaign. Discussion We have shown that a concerted, multi-pronged approach to ITN delivery in rural areas of Kenya over 3 y resulted in over 60% of children sleeping under a net treated with insecticide, surpassing the original RBM target set in Abuja in 2000 [3]. However, at the end of 2004 this target seemed almost unattainable, with only 7% of rural children reported to be sleeping under an ITN and only 3% among the poorest sectors of these communities. Radical changes in bilateral support to PSI to adapt their social marketing strategy to included MCH clinics resulted in important changes in ITN coverage (24%) by the end of 2005, but coverage still favoured the least poor children. The most dramatic increases in ITN coverage were seen during the last year of the surveillance period at the end of 2006. Through two single mass campaigns in July and September 2006, coverage of ITN use rose to over 67% and was particularly successful at reaching the poorest children (Tables 1 and 2). The concentration index of ITN coverage, which is a measure of inequality, decreased from 0.281 in 2004/5 to 0.000 in 2006/7, indicating an absence of inequality in net use (Figures 1 and 2; Table 1) coincidental with the expansion in different mechanisms of delivery. In recent years, there has been a consensus among national ministries of health, development partners, and other stakeholders that access to health interventions should be made pro-poor [30]. Although gaps in ITN coverage between the least- and most-poor groups have been declining elsewhere in Africa [5], the most-poor remain the least well covered. Our results show that ITN coverage among children was similar across all wealth groups by 2006/7. and nets provided through the free mass campaign actually preferentially covered children from the poorest-quintile homesteads while the heavily subsidised PSI-MCH clinic nets was considerably more equitable than the commercial social marketing (Figure 3; Table 2). Elsewhere in Africa pro-poor ITN interventions have been reported [32–35], but these efforts have been relatively small in scale. To the best of our knowledge this is the first time in Africa that a large-scale public health intervention, covering millions of people, has preferentially reached the most-poor quintiles of a community when compared to the least poor. Unlike single cross-sectional surveys of ITN coverage, the value of the present study is its longitudinal observations among the same homesteads exposed at different times to different systems of delivery. Such data help inform debates on whether ITN delivery should be free or subsidized and whether they should be provided through routine clinics, mass campaigns, or the private sector. Our data clearly show that the most effective means to rapidly scale up ITN coverage, particularly among the poor, is through targeted free distributions, preferably coincidental with other campaigns such as mass vaccination. However, it does not necessarily follow that this should represent the only mechanism by which treated nets are distributed to rural communities. The PSI programme of heavily subsidized net delivery through over 3,000 clinics since October 2004 has reported over 5 million sales of nets [20]. The complex distribution, ordering, and logistics of net commodities were run efficiently by an externally funded and managed system with the infrastructure and staff provided by the government and mission sectors [36]. Although there are no data to support the claim that the provision of subsidized nets at clinics increased use of health facilities, this may have occurred and is a similar argument used to increase attendance at mass Expanded Programme for Immunisation vaccine campaigns that provide free nets [15]. The PSI programme, however, did not reach nationally or internationally agreed targets of ITN coverage within the specified timelines. Similarly routine Expanded Programme for Immunisation services, provided free at clinics, often fail to reach their anticipated coverage targets [37]. We would argue that the constant availability of ITNs at clinics provides an essential early entry point for net use, particularly among young pregnant women who would otherwise not have access to ITNs if restricted to a single annual event targeting children as part of a mass distribution campaign. For vaccine-based programmes to retain effective herd immunity, periodic catch-up campaigns of single mass coverage of vulnerable populations are necessary. We would view this as an analogous position for effective ITN coverage. It is therefore not a question of choosing between the strategies but how to effectively combine them. Some sectors of our rural communities can afford subsidized ITNs, but when only these nets are available the most-poor access them least. It is likely that those bearing the brunt of the malaria burden in rural areas are those most distal to health services and the poorest. Provision of free nets would benefit these communities most. Our results are far less supportive of international donor-promoted efforts to expand the commercialization of ITN distribution in Africa [8,11]. This approach clearly failed to reach those most in need in Kenya, and despite aggressive marketing campaigns, and development of branded products and branded outlets, the incremental gains in ITN coverage were minimal. To effectively integrate routine versus mass campaign ITN distribution requires careful planning. It is important that when planning integrated free mass campaigns, each component of the package is not jeopardized by the other, for example delaying immunization to meet the needs of ITN distribution. In Kenya, funding for the donor-supported PSI programme ends in 2007. Funds are available from the GFATM and the World Bank Booster Programme during 2007 and 2008 to continue LLIN distribution through mass campaigns. Replacing or “permanently” treating existing non-LLINs, covering future vulnerable pregnant women and their infants and expanding to pockets of the country where coverage has remained low all require long-term sustainable financing planned against projected spatially defined needs. These combined approaches require long-term evaluations, modelled on the approach presented, to monitor the synergies between delivery strategies to make sure they retain the equity required to reach those most in need. Whether funding for combined models of delivery comes from national budgets, direct budgetary support from donors, or through mechanisms such as the GFATM, Presidents Malaria Initiative, or the World Bank is beyond the scope of this paper. What we can say is that if funding is not secured for clinic supply and catch-up mass campaigns for LLIN delivery beyond 2008 the impressive, rapid progress toward the RBM target of 80% coverage by 2010 in Kenya will be lost. Supporting Information Table S1 Asset Indicators and Their Weights Computed Using Principal Component Analysis to Construct Homestead Wealth Quintile Rankings for Each District (45 KB DOC) Click here for additional data file.
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              Spatial and temporal heterogeneity of Anopheles mosquitoes and Plasmodium falciparum transmission along the Kenyan coast.

              The seasonal dynamics and spatial distributions of Anopheles mosquitoes and Plasmodium falciparum parasites were studied for one year at 30 villages in Malindi, Kilifi, and Kwale Districts along the coast of Kenya. Anopheline mosquitoes were sampled inside houses at each site once every two months and malaria parasite prevalence in local school children was determined at the end of the entomologic survey. A total of 5,476 Anopheles gambiae s.l. and 3,461 An. funestus were collected. Species in the An. gambiae complex, identified by a polymerase chain reaction, included 81.9% An. gambiae s.s., 12.8% An. arabiensis, and 5.3% An. merus. Anopheles gambiae s.s. contributed most to the transmission of P. falciparum along the coast as a whole, while An. funestus accounted for more than 50% of all transmission in Kwale District. Large spatial heterogeneity of transmission intensity (< 1 up to 120 infective bites per person per year) resulted in correspondingly large and significantly related variations in parasite prevalence (range = 38-83%). Thirty-two percent of the sites (7 of 22 sites) with malaria prevalences ranging from 38% to 70% had annual entomologic inoculation rates (EIR) less than five infective bites per person per year. Anopheles gambiae s.l. and An. funestus densities in Kwale were not significantly influenced by rainfall. However, both were positively correlated with rainfall one and three months previously in Malindi and Kilifi Districts, respectively. These unexpected variations in the relationship between mosquito populations and rainfall suggest environmental heterogeneity in the predominant aquatic habitats in each district. One important conclusion is that the highly non-linear relationship between EIRs and prevalence indicates that the consistent pattern of high prevalence might be governed by substantial variation in transmission intensity measured by entomologic surveys. The field-based estimate of entomologic parameters on a district level does not provide a sensitive indicator of transmission intensity in this study.

                Author and article information

                Malar J
                Malar. J
                Malaria Journal
                BioMed Central
                1 February 2013
                : 12
                : 46
                [1 ]Department of Environmental Studies, Emory University, Atlanta, Georgia
                [2 ]Department of Public Health, School of Health Sciences, Kenyatta University, Nairobi, Kenya
                [3 ]Center for Global Health and Diseases, Case Western Reserve University, Cleveland, Ohio, USA
                [4 ]Division of Vector Borne and Neglected Tropical Diseases (DVBNTD), Ministry of Public Health and Sanitation, Nairobi, Kenya
                Copyright ©2013 Mutuku et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


                Infectious disease & Microbiology


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