Reduction in malaria burden following the introduction of indoor residual spraying in areas protected by long-lasting insecticidal nets in Western Kenya, 2016-2018.

BACKGROUND: Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are the main malaria vector control measures deployed in Kenya. Widespread pyrethroid resistance among the primary vectors in Western Kenya has necessitated the re-introduction of IRS using an organophosphate insecticide, pirimiphos-methyl (Actellic® 300CS), as a pyrethroid resistance management strategy. Evaluation of the effectiveness of the combined use of non-pyrethroid IRS and LLINs has yielded varied results. We aimed to evaluate the effect of non-pyrethroid IRS and LLINs on malaria indicators in a high malaria transmission area. METHODS: We reviewed records and tallied monthly aggregate of outpatient department (OPD) attendance, suspected malaria cases, those tested for malaria and those testing positive for malaria at two health facilities, one from Nyatike, an intervention sub-county, and one from Suba, a comparison sub-county, both located in Western Kenya, from February 1, 2016, through March 31, 2018. The first round of IRS was conducted in February-March 2017 in Nyatike sub-county and the second round one year later in both Nyatike and Suba sub-counties. The mass distribution of LLINs has been conducted in both locations. We performed descriptive analysis and estimated the effect of the interventions and temporal changes of malaria indicators using Poisson regression for a period before and after the first round of IRS. RESULTS: A higher reduction in the intervention area in total OPD, the proportion of OPD visits due to suspected malaria, testing positivity rate and annual malaria incidences were observed except for the total OPD visits among the under 5 children (59% decrease observed in the comparison area vs 33% decrease in the intervention area, net change -27%, P <0.001). The percentage decline in annual malaria incidence observed in the intervention area was more than twice the observed percentage decline in the comparison area across all the age groups. A marked decline in the monthly testing positivity rate (TPR) was noticed in the intervention area, while no major changes were observed in the comparison area. The monthly TPR reduced from 46% in February 2016 to 11% in February 2018, representing a 76% absolute decrease in TPR among all ages (RR = 0.24, 95% CI 0.12-0.46). In the comparison area, TPR was 16% in both February 2016 and February 2018 (RR = 1.0, 95% CI 0.52-2.09). A month-by-month comparison revealed lower TPR in Year 2 compared to Year 1 in the intervention area for most of the one year after the introduction of the IRS. CONCLUSIONS: Our findings demonstrated a reduced malaria burden among populations protected by both non-pyrethroid IRS and LLINs implying a possible additional benefit afforded by the combined intervention in the malaria-endemic zone.

Spatio-temporal analysis of Plasmodium falciparum prevalence to understand the past and chart the future of malaria control in Kenya.

BACKGROUND: Spatial and temporal malaria risk maps are essential tools to monitor the impact of control, evaluate priority areas to reorient intervention approaches and investments in malaria endemic countries. Here, the analysis of 36 years data on Plasmodium falciparum prevalence is used to understand the past and chart a future for malaria control in Kenya by confidently highlighting areas within important policy relevant thresholds to allow either the revision of malaria strategies to those that support pre-elimination or those that require additional control efforts. METHODS: Plasmodium falciparum parasite prevalence (PfPR) surveys undertaken in Kenya between 1980 and 2015 were assembled. A spatio-temporal geostatistical model was fitted to predict annual malaria risk for children aged 2-10 years (PfPR2-10) at 1 × 1 km spatial resolution from 1990 to 2015. Changing PfPR2-10 was compared against plausible explanatory variables. The fitted model was used to categorize areas with varying degrees of prediction probability for two important policy thresholds PfPR2-10 < 1% (non-exceedance probability) or ≥ 30% (exceedance probability). RESULTS: 5020 surveys at 3701 communities were assembled. Nationally, there was an 88% reduction in the mean modelled PfPR2-10 from 21.2% (ICR: 13.8-32.1%) in 1990 to 2.6% (ICR: 1.8-3.9%) in 2015. The most significant decline began in 2003. Declining prevalence was not equal across the country and did not directly coincide with scaled vector control coverage or changing therapeutics. Over the period 2013-2015, of Kenya's 47 counties, 23 had an average PfPR2-10 of < 1%; four counties remained ≥ 30%. Using a metric of 80% probability, 8.5% of Kenya's 2015 population live in areas with PfPR2-10 ≥ 30%; while 61% live in areas where PfPR2-10 is < 1%. CONCLUSIONS: Kenya has made substantial progress in reducing the prevalence of malaria over the last 26 years. Areas today confidently and consistently with < 1% prevalence require a revised approach to control and a possible consideration of strategies that support pre-elimination. Conversely, there remains several intractable areas where current levels and approaches to control might be inadequate. The modelling approaches presented here allow the Ministry of Health opportunities to consider data-driven model certainty in defining their future spatial targeting of resources.

Monitoring health systems readiness and inpatient malaria case-management at Kenyan county hospitals.

BACKGROUND: Change of severe malaria treatment policy from quinine to artesunate, a major malaria control advance in Africa, is compromised by scarce data to monitor policy translation into practice. In Kenya, hospital surveys were implemented to monitor health systems readiness and inpatient malaria case-management. METHODS: All 47 county referral hospitals were surveyed in February and October 2016. Data collection included hospital assessments, interviews with inpatient health workers and retrospective review of patients' admission files. Analysis included 185 and 182 health workers, and 1162 and 1224 patients admitted with suspected malaria, respectively, in all 47 hospitals. Cluster-adjusted comparisons of the performance indicators with exploratory stratifications were performed. RESULTS: Malaria microscopy was universal during both surveys. Artesunate availability increased (63.8-85.1%), while retrospective stock-outs declined (46.8-19.2%). No significant changes were observed in the coverage of artesunate trained (42.2% vs 40.7%) and supervised health workers (8.7% vs 12.8%). The knowledge about treatment policy improved (73.5-85.7%; p = 0.002) while correct artesunate dosing knowledge increased for patients < 20 kg (42.7-64.6%; p < 0.001) and > 20 kg (70.3-80.8%; p = 0.052). Most patients were tested on admission (88.6% vs 92.1%; p = 0.080) while repeated malaria testing was low (5.2% vs 8.1%; p = 0.034). Artesunate treatment for confirmed severe malaria patients significantly increased (69.9-78.7%; p = 0.030). No changes were observed in artemether-lumefantrine treatment for non-severe test positive patients (8.0% vs 8.8%; p = 0.796). Among test negative patients, increased adherence to test results was observed for non-severe (68.6-78.0%; p = 0.063) but not for severe patients (59.1-62.1%; p = 0.673). Overall quality of malaria case-management improved (48.6-56.3%; p = 0.004), both for children (54.1-61.5%; p = 0.019) and adults (43.0-51.0%; p = 0.041), and in both high (51.1-58.1%; p = 0.024) and low malaria risk areas (47.5-56.0%; p = 0.029). CONCLUSION: Most health systems and malaria case-management indicators improved during 2016. Gaps, often specific to different inpatient populations and risk areas, however remain and further programmatic interventions including close monitoring is needed to optimize policy translation.

Fever case management at private health facilities and private pharmacies on the Kenyan coast: analysis of data from two rounds of client exit interviews and mystery client visits.

BACKGROUND: Private sector availability and use of malaria rapid diagnostic tests (RDTs) lags behind the public sector in Kenya. Increasing channels through which quality malaria diagnostic services are available can improve access to testing and help meet the target of universal diagnostic testing. Registered pharmacies are currently not permitted to perform blood tests, and evidence of whether malaria RDTs can be used by non-laboratory private providers in line with the national malaria control guidelines is required to inform ongoing policy discussions in Kenya. METHODS: Two rounds of descriptive cross-sectional exit interviews and mystery client surveys were conducted at private health facilities and registered pharmacies in 2014 and 2015, 6 and 18 months into a multi-country project to prime the private sector market for the introduction of RDTs. Data were collected on reported RDT use, medicines received and prescribed, and case management of malaria test-negative mystery clients. Analysis compared outcomes at facilities and pharmacies independently for the two survey rounds. RESULTS: Across two rounds, 534 and 633 clients (including patients) from 130 and 120 outlets were interviewed, and 214 and 250 mystery client visits were completed. Reported testing by any malaria diagnostic test was higher in private health facilities than registered pharmacies in both rounds (2014: 85.6% vs. 60.8%, p < 0.001; 2015: 85.3% vs. 56.3%, p < 0.001). In registered pharmacies, testing by RDT was 52.1% in 2014 and 56.3% in 2015. At least 75% of test-positive patients received artemisinin-based combination therapy (ACT) in both rounds, with no significant difference between outlet types in either round. Provision of any anti-malarial for test-negative patients ranged from 0 to 13.9% across outlet types and rounds. In 2015, mystery clients received the correct (negative) diagnosis and did not receive an anti-malarial in 75.5% of visits to private health facilities and in 78.4% of visits to registered pharmacies. CONCLUSIONS: Non-laboratory staff working in registered pharmacies in Kenya can follow national guidelines for diagnosis with RDTs when provided with the same level of training and supervision as private health facility staff. Performance and compliance to treatment recommendations are comparable to diagnostic testing outcomes recorded in private health facilities.

The malaria testing and treatment landscape in Kenya: results from a nationally representative survey among the public and private sector in 2016.

BACKGROUND: Since 2004, Kenya's national malaria treatment guidelines have stipulated artemisinin-based combination therapy (ACT) as first-line treatment for uncomplicated malaria, and since 2014, confirmatory diagnosis of malaria in all cases before treatment has been recommended. A number of strategies to support national guidelines have been implemented in the public and private sectors in recent years. A nationally-representative malaria outlet survey, implemented across four epidemiological zones, was conducted between June and August 2016 to provide practical evidence to inform strategies and policies in Kenya towards achieving national malaria control goals. RESULTS: A total of 17,852 outlets were screened and 2271 outlets were eligible and interviewed. 78.3% of all screened public health facilities stocked both malaria diagnostic testing and quality-assured ACT (QAACT). Sulfadoxine-pyrimethamine (SP) for intermittent preventive treatment in pregnancy was available in 70% of public health facilities in endemic areas where it is recommended for treatment. SP was rarely found in the public sector outside of the endemic areas (< 0.5%). The anti-malaria stocking private sector had lower levels of QAACT (46.7%) and malaria blood testing (20.8%) availability but accounted for majority of anti-malarial distribution (70.6% of the national market share). More than 40% of anti-malarials were distributed by unregistered pharmacies (37.3%) and general retailers (7.1%). QAACT accounted for 58.2% of the total anti-malarial market share, while market share for non-QAACT was 15.8% and for SP, 24.8%. In endemic areas, 74.9% of anti-malarials distributed were QAACT. Elsewhere, QAACT market share was 49.4% in the endemic-prone areas, 33.2% in seasonal-transmission areas and 37.9% in low-risk areas. CONCLUSION: Although public sector availability of QAACT and malaria diagnosis is relatively high, there is a gap in availability of both testing and treatment that must be addressed. The private sector in Kenya, where the majority of anti-malarials are distributed, is also critical for achieving universal coverage with appropriate malaria case management. There is need for a renewed commitment and effective strategies to ensure access to affordable QAACT and confirmatory testing in the private sector, and should consider how to address malaria case management among informal providers responsible for a substantial proportion of the anti-malarial market share.

A national health facility survey of malaria infection among febrile patients in Kenya, 2014.

BACKGROUND: The use of malaria infection prevalence among febrile patients at clinics has a potential to be a valuable epidemiological surveillance tool. However, routine data are incomplete and not all fevers are tested. This study was designed to screen all fevers for malaria infection in Kenya to explore the epidemiology of fever test positivity rates. METHODS: Random sampling was used within five malaria epidemiological zones of Kenya (i.e., high lake endemic, moderate coast endemic, highland epidemic, seasonal low transmission and low risk zones). The selected sample was representative of the number of hospitals, health centres and dispensaries within each zone. Fifty patients with fever presenting to each sampled health facility during the short rainy season were screened for malaria infection using a rapid diagnostic test (RDT). Details of age, pregnancy status and basic demographics were recorded for each patient screened. RESULTS: 10,557 febrile patients presenting to out-patient clinics at 234 health facilities were screened for malaria infection. 1633 (15.5%) of the patients surveyed were RDT positive for malaria at 124 (53.0%) facilities. Infection prevalence among non-pregnant patients varied between malaria risk zones, ranging from 0.6% in the low risk zone to 41.6% in the high lake endemic zone. Test positivity rates (TPR) by age group reflected the differences in the intensity of transmission between epidemiological zones. In the lake endemic zone, 6% of all infections were among children aged less than 1 year, compared to 3% in the coast endemic, 1% in the highland epidemic zone, less than 1% in the seasonal low transmission zone and 0% in the low risk zone. Test positivity rate was 31% among febrile pregnant women in the high lake endemic zone compared to 9% in the coast endemic and highland epidemic zones, 3.2% in the seasonal low transmission zone and zero in the low risk zone. CONCLUSION: Malaria infection rates among febrile patients, with supporting data on age and pregnancy status presenting to clinics in Kenya can provide invaluable epidemiological data on spatial heterogeneity of malaria and serve as replacements to more expensive community-based infection rates to plan and monitor malaria control.

Factors influencing malaria control policy-making in Kenya, Uganda and Tanzania.

BACKGROUND: Policy decisions for malaria control are often difficult to make as decision-makers have to carefully consider an array of options and respond to the needs of a large number of stakeholders. This study assessed the factors and specific objectives that influence malaria control policy decisions, as a crucial first step towards developing an inclusive malaria decision analysis support tool (MDAST). METHODS: Country-specific stakeholder engagement activities using structured questionnaires were carried out in Kenya, Uganda and Tanzania. The survey respondents were drawn from a non-random purposeful sample of stakeholders, targeting individuals in ministries and non-governmental organizations whose policy decisions and actions are likely to have an impact on the status of malaria. Summary statistics across the three countries are presented in aggregate. RESULTS: Important findings aggregated across countries included a belief that donor preferences and agendas were exerting too much influence on malaria policies in the countries. Respondents on average also thought that some relevant objectives such as engaging members of parliament by the agency responsible for malaria control in a particular country were not being given enough consideration in malaria decision-making. Factors found to influence decisions regarding specific malaria control strategies included donor agendas, costs, effectiveness of interventions, health and environmental impacts, compliance and/acceptance, financial sustainability, and vector resistance to insecticides. CONCLUSION: Malaria control decision-makers in Kenya, Uganda and Tanzania take into account health and environmental impacts as well as cost implications of different intervention strategies. Further engagement of government legislators and other policy makers is needed in order to increase funding from domestic sources, reduce donor dependence, sustain interventions and consolidate current gains in malaria.

Bed net ownership in Kenya: the impact of 3.4 million free bed nets.

BACKGROUND: In July and September 2006, 3.4 million long-lasting insecticide-treated bed nets (LLINs) were distributed free in a campaign targeting children 0-59 months old (CU5s) in the 46 districts with malaria in Kenya. A survey was conducted one month after the distribution to evaluate who received campaign LLINs, who owned insecticide-treated bed nets and other bed nets received through other channels, and how these nets were being used. The feasibility of a distribution strategy aimed at a high-risk target group to meet bed net ownership and usage targets is evaluated. METHODS: A stratified, two-stage cluster survey sampled districts and enumeration areas with probability proportional to size. Handheld computers (PDAs) with attached global positioning systems (GPS) were used to develop the sampling frame, guide interviewers back to chosen households, and collect survey data. RESULTS: In targeted areas, 67.5% (95% CI: 64.6, 70.3%) of all households with CU5s received campaign LLINs. Including previously owned nets, 74.4% (95% CI: 71.8, 77.0%) of all households with CU5s had an ITN. Over half of CU5s (51.7%, 95% CI: 48.8, 54.7%) slept under an ITN during the previous evening. Nearly forty percent (39.1%) of all households received a campaign net, elevating overall household ownership of ITNs to 50.7% (95% CI: 48.4, 52.9%). CONCLUSIONS: The campaign was successful in reaching the target population, families with CU5s, the risk group most vulnerable to malaria. Targeted distribution strategies will help Kenya approach indicator targets, but will need to be combined with other strategies to achieve desired population coverage levels.