Titel Deelnemers "Korte inhoud" "Regional heterogeneity of malaria prevalence and associated risk factors among children under five in Togo: evidence from a national malaria indicators survey" "Gountante Kombate, Wakpaouyare Gmakouba, Susana Scott, Komi Ameko Azianu, Didier Koumavi Ekouevi, Marianne van der Sande" "BACKGROUND: Malaria remains a major cause of morbidity and death among children less than 5 years of age. In Togo, despite intensification of malaria control interventions, malaria remained highly prevalent, with significant heterogeneity from one region to another. The aim of this study is to explore further such regional differences in malaria prevalence and to determine associated risk factors.METHODS: Data from a 2017 cross-sectional nationally representative malaria indicator survey was used. Children aged 6-59 months in selected households were tested for malaria using a rapid diagnostic test (RDT), confirmed by microscopy. Univariate and multivariate logistic regression analysis were performed using Generalized Linear Models.RESULTS: A total of 2131 children aged 6-59 months (1983 in rural areas, 989 in urban areas) were enrolled. Overall 28% of children tested positive for malaria, ranging from 7.0% in the Lomé Commune region to 4% 7.1 in the Plateaux region. In multivariate analysis, statistically significant differences between regions persisted. Independent risk factors identified were higher children aged (aOR = 1.46, 95% CI [1.13-1.88]) for those above 24 months compared to those below; households wealth quintile (aOR = 0.22, 95% CI [0.11-0.41]) for those richest compared to those poorest quintiles; residence in rural areas (aOR = 2.02, 95% CI [1.32-3.13]).CONCLUSION: Interventions that target use of combined prevention measures should prioritise on older children living in poorest households in rural areas, particularly in the regions of high malaria prevalence." "Malaria micro-stratification using routine surveillance data in Western Kenya" "Victor A Alegana, Laurissa Suiyanka, Peter Macharia, Grace Ikahu-Muchangi, Robert W Snow" "BACKGROUND: There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya.METHODS: Routine data from health facilities (n = 1804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility.RESULTS: The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability" "Maplaria: a user friendly web-application for spatio-temporal malaria prevalence mapping" "Emanuele Giorgi, Peter Macharia, Jack Woodmansey, Robert W Snow, Barry Rowlingson" "BACKGROUND: Model-based geostatistical (MBG) methods have been extensively used to map malaria risk using community survey data in low-resource settings where disease registries are incomplete or non-existent. However, the wider adoption of MBG methods by national control programmes to inform health policy decisions is hindered by the lack of advanced statistical expertise and suitable computational equipment. Here, Maplaria, an interactive, user-friendly web-application that allows users to upload their own malaria prevalence data and carry out geostatistical prediction of annual malaria prevalence at any desired spatial scale, is introduced.METHODS: In the design of the Maplaria web application, two main criteria were considered: the application should be able to classify subnational divisions into the most likely endemicity levels; the web application should allow only minimal input from the user in the set-up of the geostatistical inference process. To achieve this, the process of fitting and validating the geostatistical models is carried out by statistical experts using publicly available malaria survey data from the Harvard database. The stage of geostatistical prediction is entirely user-driven and allows the user to upload malaria data, as well as vector data that define the administrative boundaries for the generation of spatially aggregated inferences.RESULTS: The process of data uploading and processing is split into a series of steps spread across screens through the progressive disclosure technique that prevents the user being immediately overwhelmed by the length of the form. Each of these is illustrated using a data set from the Malaria Indicator carried out in Tanzania in 2017 as an example.CONCLUSIONS: Maplaria application provides a user-friendly solution to the problem making geostatistical methods more accessible to users that have not undertaken formal training in statistics. The application is a useful tool that can be used to foster ownership, among policy makers, of disease risk maps and promote better use of data for decision-making in low resource settings." "Spatial and spatio-temporal methods for mapping malaria risk: a systematic review" "Julius Nyerere Odhiambo, Chester Kalinda, Peter Macharia, Robert W Snow, Benn Sartorius" "BACKGROUND: Approaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of the methods and covariates used to map malaria risk has not been undertaken. Therefore, this review aimed to systematically retrieve, summarise methods and examine covariates that have been used for mapping malaria risk in sub-Saharan Africa (SSA).METHODS: A systematic search of malaria risk mapping studies was conducted using PubMed, EBSCOhost, Web of Science and Scopus databases. The search was restricted to refereed studies published in English from January 1968 to April 2020. To ensure completeness, a manual search through the reference lists of selected studies was also undertaken. Two independent reviewers completed each of the review phases namely: identification of relevant studies based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, data extraction and methodological quality assessment using a validated scoring criterion.RESULTS: One hundred and seven studies met the inclusion criteria. The median quality score across studies was 12/16 (range: 7-16). Approximately half (44%) of the studies employed variable selection techniques prior to mapping with rainfall and temperature selected in over 50% of the studies. Malaria incidence (47%) and prevalence (35%) were the most commonly mapped outcomes, with Bayesian geostatistical models often (31%) the preferred approach to risk mapping. Additionally, 29% of the studies employed various spatial clustering methods to explore the geographical variation of malaria patterns, with Kulldorf scan statistic being the most common. Model validation was specified in 53 (50%) studies, with partitioning data into training and validation sets being the common approach.CONCLUSIONS: Our review highlights the methodological diversity prominent in malaria risk mapping across SSA. To ensure reproducibility and quality science, best practices and transparent approaches should be adopted when selecting the statistical framework and covariates for malaria risk mapping. Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology." "Social determinants of malaria in an endemic area of Indonesia" "Hamzah Hasyim, Pat Dale, David Alexander Groneberg, Ulrich Kuch, Ruth Müller" "Background: Malaria is an increasing concern in Indonesia. Socio-demographic factors were found to strongly influence malaria prevalence. This research aimed to explore the associations between socio-demographic factors and malaria prevalence in Indonesia.Methods: The study used a cross-sectional design and analysed relationships among the explanatory variables of malaria prevalence in five endemic provinces using multivariable logistic regression.Results: The analysis of baseline socio-demographic data revealed the following independent risk variables related to malaria prevalence: gender, age, occupation, knowledge of the availability of healthcare services, measures taken to protect from mosquito bites, and housing condition of study participants. Multivariable analysis showed that participants who were unaware of the availability of health facilities were 4.2 times more likely to have malaria than those who were aware of the health facilities (adjusted odds ratio = 4.18; 95% CI 1.52-11.45; P = 0.005).Conclusions: Factors that can be managed and would favour malaria elimination include a range of prevention behaviours at the individual level and using the networks at the community level of primary healthcare centres. This study suggests that improving the availability of a variety of health facilities in endemic areas, information about their services, and access to these is essential." "Targeting remaining pockets of malaria transmission in Kenya to hasten progress towards national elimination goals: an assessment of prevalence and risk factors in children from the Lake endemic region" "Ismail Mahat Bashir, Nancy Nyakoe, Marianne van der Sande" "Background: With an overall decline of malaria incidence, elimination of malaria is gradually becoming the next target for many of countries affected by the disease. In Kenya the national malaria control strategy is aiming to reach pre-elimination for most parts of the country. However, considerable heterogeneity in prevalence of the disease within the country and especially the remaining high prevalent region of the Lake endemic region is likely to slow progress towards this target. To achieve a sustained control and an eventual elimination, a clear understanding of drivers of ongoing malaria transmission in remaining hotspots is needed.Methods: Data from the 2015 Malaria Indicator Survey (MIS) were analysed for prevalence of malaria parasitaemia in children (6 months to 14 years) of different countries within the highly endemic Lake region. Univariate and multivariate logistic regression analysis were preformed to explore associations between selected risk factors and being parasitaemic. A predictive model was built for the association between malaria and the risk factors with the aim of identifying heterogeneities of the disease at the lower administrative levels.Results: Overall, 604/2253 (27%, 95% CI 21.8-32.2) children were parasitaemic. The highest prevalence was observed in Busia County (37%) and lowest in Bungoma County (18%). Multivariate logistic regression analysis showed that the 10-14 years age group (OR=3.0, 95% CI 2.3-4.1), households in the poorest socio-economic class (OR=2.1, 95% CI 1.3-3.3), farming (OR=1.4, 95% CI 1.2-2.5) and residence in Busia (OR=4.6, 95% CI 2.1-8.2), Kakamega (OR=2.6, 95% CI 1.3-5.4), and Migori counties (OR=4.6 95% CI 2.1-10.3) were associated with higher risk of parasitaemia. Having slept under a long-lasting insecticide-treated bed net (LLIN) was associated with a lower risk (OR=0.7, 95% CI 0.6-0.9). No association were found between malaria infection and the gender of the child, the household head, and the education status of the household head.Discussion and conclusion: Detailed analysis of malaria prevalence data in a hotspot area can identify new threats and avail opportunities for directing intervention. In the Lake endemic region of Kenya, interventions should be focused more on counties with the highest prevalence, and should target older children as well as children from the lower socio-economic strata. Precisely targeting interventions in remaining hotspots and high-risk populations will likely make impact and accelerate progress towards pre-elimination targets." "Coverage of routine reporting on malaria parasitological testing in Kenya, 2015-2016" "Joseph K Maina, Peter Macharia, Paul O Ouma, Robert W Snow, Emelda A Okiro" "BACKGROUND: Following the launch of District Health Information System 2 across facilities in Kenya, more health facilities are now capable of carrying out malaria parasitological testing and reporting data as part of routine health information systems, improving the potential value of routine data for accurate and timely tracking of rapidly changing disease epidemiology at fine spatial resolutions.OBJECTIVES: This study evaluates the current coverage and completeness of reported malaria parasitological testing data in DHIS2 specifically looking at patterns in geographic coverage of public health facilities in Kenya.METHODS: Monthly facility level data on malaria parasitological testing were extracted from Kenya DHIS2 between November 2015 and October 2016. DHIS2 public facilities were matched to a geo-coded master facility list to obtain coordinates. Coverage was defined as the geographic distribution of facilities reporting any data by region. Completeness of reporting was defined as the percentage of facilities reporting any data for the whole 12-month period or for 3, 6 and 9 months.RESULTS: Public health facilities were 5,933 (59%) of 10,090 extracted. Fifty-nine per Cent of the public facilities did not report any data while 36, 29 and 22% facilities had data reported at least 3, 6 and 9 months, respectively. Only 8% of public facilities had data reported for every month. There were proportionately more hospitals (86%) than health centres (76%) and dispensaries/clinics (30%) reporting. There were significant geographic variations in reporting rates. Counties along the malaria endemic coast had the lowest reporting rate with only 1% of facilities reporting consistently for 12 months.CONCLUSION: Current coverage and completeness of reporting of malaria parasitological diagnosis across Kenya's public health system remains poor. The usefulness of routine data to improve our understanding of sub-national heterogeneity across Kenya would require significant improvements to the consistency and coverage of data captured by DHIS2." "Spectrum of imported infectious diseases: a comparative prevalence study of 16,817 German travelers and 977 immigrants from the tropics and subtropics" "Karl-Heinz Herbinger, Martin Alberer, Nicole Berens-Riha, Mirjam Schunk, Gisela Bretzel, Frank von Sonnenburg, Hans-Dieter Nothdurft, Thomas Löscher, Marcus Beissner" "The aim of this study was to assess the spectrum of imported infectious diseases (IDs) among patients consulting the University of Munich, Germany, between 1999 and 2014 after being in the sub-/tropics. The analysis investigated complete data sets of 16,817 diseased German travelers (2,318 business travelers, 4,029 all-inclusive travelers, and 10,470 backpackers) returning from Latin America (3,225), Africa (4,865), or Asia (8,727), and 977 diseased immigrants, originating from the same regions (112, 654 and 211 respectively). The most frequent symptoms assessed were diarrhea (38%), fever (29%), and skin disorder (22%). The most frequent IDs detected were intestinal infections with species of Blastocystis(900),Giardia(730),Campylobacter(556),Shigella(209), and Salmonella(183). Also frequently observed were cutaneous larva migrans (379), dengue (257), and malaria (160). The number of IDs with significantly elevated proportions was higher among backpackers (18) and immigrants (17), especially among those from Africa (18) and Asia (17), whereas it was lower for business travelers (5), all-inclusive travelers (1), and those from Latin America (5). This study demonstrates a large spectrum of imported IDs among returning German travelers and immigrants, which varies greatly based not only on travel destination and origin of immigrants, but also on type of travel." "A national health facility survey of malaria infection among febrile patients in Kenya, 2014" "Sophie Githinji, Abdisalan M Noor, Josephine Malinga, Peter Macharia, Rebecca Kiptui, Ahmeddin Omar, Kiambo Njagi, Ejersa Waqo, Robert W Snow" "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." "Potential impact of co-infections and co-morbidities prevalent in Africa on influenza severity and frequency: a systematic review" "Adam L Cohen, Meredith Mcmorrow, Sibongile Walaza, Cheryl Cohen, STEFANO TEMPIA, Marissa Alexander-Scott, Marc-Alain Widdowson" "Infectious diseases and underlying medical conditions common to Africa may affect influenza frequency and severity. We conducted a systematic review of published studies on influenza and the following co-infections or co-morbidities that are prevalent in Africa: dengue, malaria, measles, meningococcus, Pneumocystis jirovecii pneumonia (PCP), hemoglobinopathies, and malnutrition. Articles were identified except for influenza and PCP. Very few studies were from Africa. Sickle cell disease, dengue, and measles co-infection were found to increase the severity of influenza disease, though this is based on few studies of dengue and measles and the measles study was of low quality. The frequency of influenza was increased among patients with sickle cell disease. Influenza infection increased the frequency of meningococcal disease. Studies on malaria and malnutrition found mixed results. Age-adjusted morbidity and mortality from influenza may be more common in Africa because infections and diseases common in the region lead to more severe outcomes and increase the influenza burden. However, gaps exist in our knowledge about these interactions."