BackgroundHealth 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.MethodsData 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.ResultsMalaria 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.ConclusionsThere 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-017-1973-y) contains supplementary material, which is available to authorized users.

BackgroundSpatial 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.MethodsPlasmodium 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).Results5020 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%.ConclusionsKenya 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.Electronic supplementary materialThe online version of this article (10.1186/s12936-018-2489-9) contains supplementary material, which is available to authorized users.

BackgroundPrivate 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.MethodsTwo 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.ResultsAcross 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.ConclusionsNon-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.

BackgroundChange 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.MethodsAll 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.ResultsMalaria 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).ConclusionMost 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.

BackgroundThe 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.MethodsRandom 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.Results10,557 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.ConclusionMalaria 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.

BackgroundSince 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.ResultsA 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.ConclusionAlthough 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.Electronic supplementary materialThe online version of this article (10.1186/s12936-017-2089-0) contains supplementary material, which is available to authorized users.

BackgroundThe World Health Organization recommends that long-lasting insecticidal nets (LLINs) for malaria prevention should be distributed continuously through antenatal care (ANC) and the expanded programme on immunization (EPI) in addition to mass campaigns. Despite these recommendations, the continuous distribution (CD) of LLIN distribution through ANC and EPI is not policy in many countries, and where there is a policy, implementation is incomplete. This study aims to identify the operational strengths and weaknesses of LLINs CD in four country programmes in sub-Saharan Africa.MethodsA qualitative rapid assessment process was conducted using semi-structured individual and group interviews at the national, sub-national, and facility level in four countries. Seventy participants were included (23 in Kenya, 13 in Malawi, 18 in Mali and 16 in Rwanda), drawn from malaria programmes, ANC and EPI programmes, government logistics units, and partner organizations. Interviews were structured to identify themes within a health systems approach. Policy and guideline documents and data collection tools were reviewed as a means of triangulation. Data analysis focused on pre-determined and emergent themes.ResultsThe four countries used a wide variety of management systems for the supply of LLINs to routine services. Issues related to quantification, supply logistics and data collection all contributed to stock-outs at facility level. None of the four countries had guidelines for responding to stock-outs or system enabling local staff to request additional supplies of LLINs. In all four countries, data collection of LLIN distribution was incomplete or absent at facility level, and such data were not used for planning. Training of staff at the facility level was implemented less frequently than national and sub-national staff would have preferred. Logistics systems, independent of other commodities, and in-country partner support strengthened the continuous distribution of LLINs.ConclusionsIn these countries, stock-outs were the most important single obstacle to the smooth operations of continuous LLIN distribution. Stock-outs can be avoided if facilities have the capacity to place orders for LLIN resupply as needed. Revised data collection and management systems for LLIN distribution have the potential to increase coverage of the target populations by improving LLIN stock-out response, and strengthening monitoring and evaluation of distribution.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1184-y) contains supplementary material, which is available to authorized users.

Opportunities for improving the distribution of LLINs through these channels exist, especially in the case of EPI. For both ANC and EPI, integrated distribution of LLINs has the potential to act as an incentive, improving the already strong coverage of both these essential services. The collection and reporting of data on LLINs distributed through the ANC and EPI can provide insight into the performance of LLIN distribution within these programmes. Greater attention to data collection and use, by both the global malaria community, and the integrated programmes, can improve this distribution channel strength and effectiveness.