25 research outputs found

    Large-scale implementation of disease control programmes: a cost-effectiveness analysis of long-lasting insecticide-treated bed net distribution channels in a malaria-endemic area of western Kenya-a study protocol.

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    Introduction Historically, Kenya has used various distribution models for long-lasting insecticide-treated bed nets (LLINs) with variable results in population coverage. The models presently vary widely in scale, target population and strategy. There is limited information to determine the best combination of distribution models, which will lead to sustained high coverage and are operationally efficient and cost-effective. Standardised cost information is needed in combination with programme effectiveness estimates to judge the efficiency of LLIN distribution models and options for improvement in implementing malaria control programmes. The study aims to address the information gap, estimating distribution cost and the effectiveness of different LLIN distribution models, and comparing them in an economic evaluation. Methods and analysis Evaluation of cost and coverage will be determined for 5 different distribution models in Busia County, an area of perennial malaria transmission in western Kenya. Cost data will be collected retrospectively from health facilities, the Ministry of Health, donors and distributors. Programme-effectiveness data, defined as the number of people with access to an LLIN per 1000 population, will be collected through triangulation of data from a nationally representative, cross-sectional malaria survey, a cross-sectional survey administered to a subsample of beneficiaries in Busia County and LLIN distributors’ records. Descriptive statistics and regression analysis will be used for the evaluation. A cost-effectiveness analysis will be performed from a health-systems perspective, and cost-effectiveness ratios will be calculated using bootstrapping techniques. Ethics and dissemination The study has been evaluated and approved by Kenya Medical Research Institute, Scientific and Ethical Review Unit (SERU number 2997). All participants will provide written informed consent. The findings of this economic evaluation will be disseminated through peer-reviewed publications

    A cross-sectional study of the availability and price of anti-malarial medicines and malaria rapid diagnostic tests in private sector retail drug outlets in rural Western Kenya, 2013.

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    BACKGROUND Although anti-malarial medicines are free in Kenyan public health facilities, patients often seek treatment from private sector retail drug outlets. In mid-2010, the Affordable Medicines Facility-malaria (AMFm) was introduced to make quality-assured artemisinin-based combination therapy (ACT) accessible and affordable in private and public sectors. METHODS Private sector retail drug outlets stocking anti-malarial medications within a surveillance area of approximately 220,000 people in a malaria perennial high-transmission area in rural western Kenya were identified via a census in September 2013. A cross-sectional study was conducted in September-October 2013 to determine availability and price of anti-malarial medicines and malaria rapid diagnostic tests (RDTs) in drug outlets. A standardized questionnaire was administered to collect drug outlet and personnel characteristics and availability and price of anti-malarials and RDTs. RESULTS Of 181 drug outlets identified, 179 (99 %) participated in the survey. Thirteen percent were registered pharmacies, 25 % informal drug shops, 46 % general shops, 13 % homesteads and 2 % other. One hundred sixty-five (92 %) had at least one ACT type: 162 (91 %) had recommended first-line artemether-lumefantrine (AL), 22 (12 %) had recommended second-line dihydroartemisinin-piperaquine (DHA-PPQ), 85 (48 %) had sulfadoxine-pyrimethamine (SP), 60 (34 %) had any quinine (QN) formulation, and 14 (8 %) had amodiaquine (AQ) monotherapy. The mean price (range) of an adult treatment course for AL was 1.01(1.01 (0.35-4.71); DHA-PPQ was 4.39(4.39 (0.71-7.06); QN tablets were 2.24(2.24 (0.12-4.71); SP was 0.62(0.62 (0.24-2.35); AQ monotherapy was 0.42(0.42 (0.24-1.06). The mean AL price with or without the AMFm logo did not differ significantly (1.01and1.07,respectively;p = 0.45).Only17(10 1.01 and 1.07, respectively; p = 0.45). Only 17 (10 %) drug outlets had RDTs; 149 (84 %) never stocked RDTs. The mean RDT price was 0.92 ($0.24-2.35). CONCLUSIONS Most outlets never stocked RDTs; therefore, testing prior to treatment was unlikely for customers seeking treatment in the private retail sector. The recommended first-line treatment, AL, was widely available. Although SP and AQ monotherapy are not recommended for treatment, both were less expensive than AL, which might have caused preferential use by customers. Interventions that create community demand for malaria diagnostic testing prior to treatment and that increase RDT availability should be encouraged

    Malaria Parasitemia Among Febrile Patients Seeking Clinical Care at an Outpatient Health Facility in an Urban Informal Settlement Area in Nairobi, Kenya.

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    Nairobi is considered a low-risk area for malaria transmission, but travel can influence transmission of malaria. We investigated the demographic characteristics and travel history of patients with documented fever and malaria in a study clinic in a population-based surveillance system over a 5-year period, January 1, 2007 to December 31, 2011. During the study period, 11,480 (68%) febrile patients had a microscopy test performed for malaria, of which 2,553 (22%) were positive. Malaria was detected year-round with peaks in January, May, and September. Children aged 5-14 years had the highest proportion (28%) of positive results followed by children aged 1-4 years (23%). Almost two-thirds of patients with malaria reported traveling outside Nairobi; 79% of these traveled to three counties in western Kenya. History of recent travel (i.e., in past month) was associated with malaria parasitemia (odds ratio: 10.0, 95% confidence interval: 9.0-11.0). Malaria parasitemia was frequently observed among febrile patients at a health facility in the urban slum of Kibera, Nairobi. The majority of patients had traveled to western Kenya. However, 34% reported no travel history, which raises the possibility of local malaria transmission in this densely populated, urban setting. These findings have important implications for malaria control in large Nairobi settlements

    Trends in malaria prevalence and health related socioeconomic inequality in rural western Kenya: results from repeated household malaria cross-sectional surveys from 2006 to 2013

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    Objective The objective of this analysis was to examine trends in malaria parasite prevalence and related socioeconomic inequalities in malaria indicators from 2006 to 2013 during a period of intensification of malaria control interventions in Siaya County, western Kenya. Methods Data were analysed from eight independent annual cross-sectional surveys from a combined sample of 19 315 individuals selected from 7253 households. Study setting was a health and demographic surveillance area of western Kenya. Data collected included demographic factors, household assets, fever and medication use, malaria parasitaemia by microscopy, insecticide-treated bed net (ITN) use and care-seeking behaviour. Households were classified into five socioeconomic status and dichotomised into poorest households (poorest 60%) and less poor households (richest 40%). Adjusted prevalence ratios (aPR) were calculated using a multivariate generalised linear model accounting for clustering and cox proportional hazard for pooled data assuming constant follow-up time. Results Overall, malaria infection prevalence was 36.5% and was significantly higher among poorest individuals compared with the less poor (39.9% vs 33.5%, aPR=1.17; 95% CI 1.11 to 1.23) but no change in prevalence over time (trend p value <0.256). Care-seeking (61.1% vs 62.5%, aPR=0.99; 95% CI 0.95 to 1.03) and use of any medication were similar among the poorest and less poor. Poorest individuals were less likely to use Artemether-Lumefantrine or quinine for malaria treatment (18.8% vs 22.1%, aPR=0.81, 95% CI 0.72 to 0.91) while use of ITNs was lower among the poorest individuals compared with less poor (54.8% vs 57.9%; aPR=0.95; 95% CI 0.91 to 0.99), but the difference was negligible. Conclusions Despite attainment of equity in ITN use over time, socioeconomic inequalities still existed in the distribution of malaria. This might be due to a lower likelihood of treatment with an effective antimalarial and lower use of ITNs by poorest individuals. Additional strategies are necessary to reduce socioeconomic inequities in prevention and control of malaria in endemic areas in order to achieve universal health coverage and sustainable development goals

    Coverage outcomes (effects), costs, cost-effectiveness, and equity of two combinations of long-lasting insecticidal net (LLIN) distribution channels in Kenya: a two-arm study under operational conditions

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    Background: Malaria-endemic countries distribute long-lasting insecticidal nets (LLINs) through combined channels with ambitious, universal coverage (UC) targets. Kenya has used eight channels with variable results. To inform national decision-makers, this two-arm study compares coverage (effects), costs, cost-effectiveness, and equity of two combinations of LLIN distribution channels in Kenya. Methods: Two combinations of five delivery channels were compared as ‘intervention’ and ‘control’ arms. The intervention arm comprised four channels: community health volunteer (CHV), antenatal and child health clinics (ANCC), social marketing (SM) and commercial outlets (CO). The control arm consisted of the intervention arm channels except mass campaign (MC) replaced CHV. Primary analysis used random sample household survey data, service-provider costs, and voucher or LLIN distribution data to compare between-arm effects, costs, cost-effectiveness, and equity. Secondary analyses compared costs and equity by channel. Results: The multiple distribution channels used in both arms of the study achieved high LLIN ownership and use. The intervention arm had significantly lower reported LLIN use the night before the survey (84·8% [95% CI 83·0–86·4%] versus 89·2% [95% CI 87·8–90·5%], p < 0·0001), higher unit costs (10⋅56versus10·56 versus 7·17), was less cost-effective (86⋅44,9586·44, 95% range 75·77–102⋅77versus102·77 versus 69·20, 95% range 63⋅66–63·66–77·23) and more inequitable (Concentration index [C.Ind] = 0·076 [95% CI 0·057 to 0·095 versus C.Ind = 0.049 [95% CI 0·030 to 0·067]) than the control arm. Unit cost per LLIN distributed was lowest for MC (3⋅10)followedbyCHV(3·10) followed by CHV (10·81) with both channels being moderately inequitable in favour of least-poor households. Conclusion: In line with best practices, the multiple distribution channel model achieved high LLIN ownership and use in this Kenyan study setting. The control-arm combination, which included MC, was the most cost-effective way to increase UC at household level. Mass campaigns, combined with continuous distribution channels, are an effective and cost-effective way to achieve UC in Kenya. The findings are relevant to other countries and donors seeking to optimise LLIN distribution. Trial registration: The assignment of the intervention was not at the discretion of the investigators; therefore, this study did not require registration

    Knowledge and Adherence to the National Guidelines for Malaria Diagnosis in Pregnancy among Health-Care Providers and Drug-Outlet Dispensers in Rural Western Kenya

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    Prompt diagnosis and effective treatment of acute malaria in pregnancy (MiP) is important for the mother and fetus; data on health-care provider adherence to diagnostic guidelines in pregnancy are limited. From September to November 2013, a cross-sectional survey was conducted in 51 health facilities and 39 drug outlets in Western Kenya. Provider knowledge of national diagnostic guidelines for uncomplicated MiP were assessed using standardized questionnaires. The use of parasitologic testing was assessed in health facilities via exit interviews with febrile women of childbearing age and in drug outlets via simulated-client scenarios, posing as pregnant women or their spouses. Overall, 93% of providers tested for malaria or accurately described signs and symptoms consistent with clinical malaria. Malaria was parasitologically confirmed in 77% of all patients presenting with febrile illness at health facilities and 5% of simulated clients at drug outlets. Parasitological testing was available in 80% of health facilities; 92% of patients evaluated at these facilities were tested. Only 23% of drug outlets had malaria rapid diagnostic tests (RDTs); at these outlets, RDTs were offered in 17% of client simulations. No differences were observed in testing rates by pregnancy trimester. The study highlights gaps among health providers in diagnostic knowledge and practice related to MiP, and the lack of malaria diagnostic capacity, particularly in drug outlets. The most important factor associated with malaria testing of pregnant women was the availability of diagnostics at the point of service. Interventions that increase the availability of malaria diagnostic services might improve malaria case management in pregnant women

    Completeness of malaria indicator data reporting via the District Health Information Software 2 in Kenya, 2011–2015

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    Abstract Background Health facility-based data reported through routine health information systems form the primary data source for programmatic monitoring and evaluation in most developing countries. The adoption of District Health Information Software (DHIS2) has contributed to improved availability of routine health facility-based data in many low-income countries. An assessment of malaria indicators data reported by health facilities in Kenya during the first 5 years of implementation of DHIS2, from January 2011 to December 2015, was conducted. Methods Data on 19 malaria indicators reported monthly by health facilities were extracted from the online Kenya DHIS2 database. Completeness of reporting was analysed for each of the 19 malaria indicators and expressed as the percentage of data values actually reported over the expected number; all health facilities were expected to report data for each indicator for all 12 months in a year. Results Malaria indicators data were analysed for 6235 public and 3143 private health facilities. Between 2011 and 2015, completeness of reporting in the public sector increased significantly for confirmed malaria cases across all age categories (26.5–41.9%, p < 0.0001, in children aged <5 years; 30.6–51.4%, p < 0.0001, in persons aged ≥5 years). Completeness of reporting of new antenatal care (ANC) clients increased from 53.7 to 70.5%, p < 0.0001). Completeness of reporting of intermittent preventive treatment in pregnancy (IPTp) decreased from 64.8 to 53.7%, p < 0.0001 for dose 1 and from 64.6 to 53.4%, p < 0.0001 for dose 2. Data on malaria tests performed and test results were not available in DHIS2 from 2011 to 2014. In 2015, sparse data on microscopy (11.5% for children aged <5 years; 11.8% for persons aged ≥5 years) and malaria rapid diagnostic tests (RDTs) (8.1% for all ages) were reported. In the private sector, completeness of reporting increased significantly for confirmed malaria cases across all age categories (16.7–23.1%, p < 0.0001, in children aged <5 years; 19.4–28.6%, p < 0.0001, in persons aged ≥5 years). Completeness of reporting also improved for new ANC clients (16.2–23.6%, p < 0.0001), and for IPTp doses 1 and 2 (16.6–20.2%, p < 0.0001 and 15.5–20.5%, p < 0.0001, respectively). In 2015, less than 3% of data values for malaria tests performed were reported in DHIS2 from the private sector. Conclusions There have been sustained improvements in the completeness of data reported for most key malaria indicators since the adoption of DHIS2 in Kenya in 2011. However, major data gaps were identified for the malaria-test indicator and overall low reporting across all indicators from private health facilities. A package of proven DHIS2 implementation interventions and performance-based incentives should be considered to improve private-sector data reporting

    Age-Specific Malaria Mortality Rates in the KEMRI/CDC Health and Demographic Surveillance System in Western Kenya, 2003–2010

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    Recent global malaria burden modeling efforts have produced significantly different estimates, particularly in adult malaria mortality. To measure malaria control progress, accurate malaria burden estimates across age groups are necessary. We determined age-specific malaria mortality rates in western Kenya to compare with recent global estimates. We collected data from 148,000 persons in a health and demographic surveillance system from 2003–2010. Standardized verbal autopsies were conducted for all deaths; probable cause of death was assigned using the InterVA-4 model. Annual malaria mortality rates per 1,000 person-years were generated by age group. Trends were analyzed using Poisson regression. From 2003–2010, in children <5 years the malaria mortality rate decreased from 13.2 to 3.7 per 1,000 person-years; the declines were greatest in the first three years of life. In children 5–14 years, the malaria mortality rate remained stable at 0.5 per 1,000 person-years. In persons ≥15 years, the malaria mortality rate decreased from 1.5 to 0.4 per 1,000 person-years. The malaria mortality rates in young children and persons aged ≥15 years decreased dramatically from 2003–2010 in western Kenya, but rates in older children have not declined. Sharp declines in some age groups likely reflect the national scale up of malaria control interventions and rapid expansion of HIV prevention services. These data highlight the importance of age-specific malaria mortality ascertainment and support current strategies to include all age groups in malaria control interventions

    Knowledge and Adherence to the National Guidelines for Malaria Case Management in Pregnancy among Healthcare Providers and Drug Outlet Dispensers in Rural, Western Kenya.

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    BACKGROUND:Although prompt, effective treatment is a cornerstone of malaria control, information on provider adherence to malaria in pregnancy (MIP) treatment guidelines is limited. Incorrect or sub-optimal treatment can adversely affect the mother and fetus. This study assessed provider knowledge of and adherence to national case management guidelines for uncomplicated MIP. METHODS:We conducted a cross-sectional study from September to November 2013, in 51 health facilities (HF) and a randomly-selected sample of 39 drug outlets (DO) in the KEMRI/CDC Health and Demographic Surveillance System area in western Kenya. Provider knowledge of national treatment guidelines was assessed with standardized questionnaires. Correct practice required adequate diagnosis, pregnancy assessment, and treatment with correct drug and dosage. In HF, we conducted exit interviews in all women of childbearing age assessed for fever. In DO, simulated clients posing as first trimester pregnant women or as relatives of third trimester pregnant women collected standardized information. RESULTS:Correct MIP case management knowledge and practice were observed in 45% and 31% of HF and 0% and 3% of DO encounters, respectively. The correct drug and dosage for pregnancy trimester was prescribed in 62% of HF and 42% of DO encounters; correct prescription occurred less often in first than in second/ third trimesters (HF: 24% vs. 65%, p<0.01; DO: 0% vs. 40%, p<0.01). Sulfadoxine-pyrimethamine, which is not recommended for malaria treatment, was prescribed in 3% of HF and 18% of DO encounters. Exposure to artemether-lumefantrine in first trimester, which is contraindicated, occurred in 29% and 49% of HF and DO encounters, respectively. CONCLUSION:This study highlights knowledge inadequacies and incorrect prescribing practices in the treatment of MIP. Particularly concerning is the prescription of contraindicated medications in the first trimester. These issues should be addressed through comprehensive trainings and increased supportive supervision. Additional innovative means to improve care should be explored

    Factors associated with malaria microscopy diagnostic performance following a pilot quality-assurance programme in health facilities in malaria low-transmission areas of Kenya, 2014

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    Abstract Background Malaria accounts for ~21% of outpatient visits annually in Kenya; prompt and accurate malaria diagnosis is critical to ensure proper treatment. In 2013, formal malaria microscopy refresher training for microscopists and a pilot quality-assurance (QA) programme for malaria diagnostics were independently implemented to improve malaria microscopy diagnosis in malaria low-transmission areas of Kenya. A study was conducted to identify factors associated with malaria microscopy performance in the same areas. Methods From March to April 2014, a cross-sectional survey was conducted in 42 public health facilities; 21 were QA-pilot facilities. In each facility, 18 malaria thick blood slides archived during January–February 2014 were selected by simple random sampling. Each malaria slide was re-examined by two expert microscopists masked to health-facility results. Expert results were used as the reference for microscopy performance measures. Logistic regression with specific random effects modelling was performed to identify factors associated with accurate malaria microscopy diagnosis. Results Of 756 malaria slides collected, 204 (27%) were read as positive by health-facility microscopists and 103 (14%) as positive by experts. Overall, 93% of slide results from QA-pilot facilities were concordant with expert reference compared to 77% in non-QA pilot facilities (p < 0.001). Recently trained microscopists in QA-pilot facilities performed better on microscopy performance measures with 97% sensitivity and 100% specificity compared to those in non-QA pilot facilities (69% sensitivity; 93% specificity; p < 0.01). The overall inter-reader agreement between QA-pilot facilities and experts was κ = 0.80 (95% CI 0.74–0.88) compared to κ = 0.35 (95% CI 0.24–0.46) between non-QA pilot facilities and experts (p < 0.001). In adjusted multivariable logistic regression analysis, recent microscopy refresher training (prevalence ratio [PR] = 13.8; 95% CI 4.6–41.4), ≥5 years of work experience (PR = 3.8; 95% CI 1.5–9.9), and pilot QA programme participation (PR = 4.3; 95% CI 1.0–11.0) were significantly associated with accurate malaria diagnosis. Conclusions Microscopists who had recently completed refresher training and worked in a QA-pilot facility performed the best overall. The QA programme and formal microscopy refresher training should be systematically implemented together to improve parasitological diagnosis of malaria by microscopy in Kenya
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