c5a227d7-2259-44ea-88aa-b6e5252cbc35 https://ipt.gbif.org/resource?r=map_historical_data_ii Test MAP historical data Marianne Sinka University of Oxford PI 0000-0001-7145-3179 Antoinette Wiebe icipe Data manager

KE

awiebe@icipe.org Marianne Sinka University of Oxford PI 0000-0001-7145-3179 Antoinette Wiebe icipe Data manager

KE

awiebe@icipe.org 2025-02-03 eng The primary goal of the Malaria Atlas Project (MAP) is to develop the science of malaria cartography. Our approach will be fi rst to defi ne the global limits of contemporary malaria transmission; we have initiated this process [1, 2], but will substantially refi ne these layers with additional medical intelligence in future years. Within these limits, we plan to then model endemicity using a global evidence base of malaria parasite prevalence. This Health in Action concentrates mostly on how we intend to achieve this important goal. Once we have created these global endemicity maps, these will then provide a baseline to facilitate estimation of populations at risk of malaria and more-credible predictions of disease burden. These maps will also provide a platform to help target intervention needs, and may provide a means to measure progress toward national and international malaria public health goals at a global scale. Occurrence Anopheles malaria modelling map distribution ecology insecticide resistance bionomics vector infectious disease. GBIF Dataset Type Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_type_2015-07-10.xml Observation GBIF Dataset Subtype Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_subtype.xml This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License. Creative Commons Attribution 4.0 International https://spdx.org/licenses/CC-BY-4.0.html CC-BY-4.0 https://ipt.gbif.org/archive.do?r=map_historical_data_ii Anopheles from Africa. -180 180 90 -90 Anopheles mosquitoes from Africa. genus Anopheles Mosquito unknown Marianne Sinka University of Oxford PI 0000-0001-7145-3179 Antoinette Wiebe icipe Data manager First round data abstraction from the collated literature; data to be entered into a pre evaluated template that allows occurrence, bionomic and IR data to be reconciled. ● Data georeferenced and checked against peripheral information given in the source ● Second round data checks repeat the data abstraction process by a second independent research assistant. ● Third round data checks by a third independent research assistant, focus on numerical abstracted data and georeferenced coordinates ● Automated data checks - all data mapped and confirmed to lie in the correctly stated country, admin area etc. Current dataset for Africa includes 38,351 records and runs from 1970 to 2015. It currently does not include all sibling species nor any data for the PSV. The MAP collaboration has adopted three linked approaches to identifying empirical PR survey data: a) a traditional electronic search using PubMed [38] with 'malaria' and MEC name as free text rather than Medical Subject Headings terms that tend to be less inclusive; b) direct contact with malaria field scientists, research institutions and control agencies in MECs identified through the PubMed search; and c) an e-mail circular, linked to the launch of the MAP website, to locate sources of information not readily accessible from the first two search strategies. Assembling a digital data archive Each source of information was reviewed by one of the authors of this paper and the data extracted into a customized Microsoft Access (Microsoft, 2003) database. A unique, auto-generated identifier links the record to a reference manager platform and to an electronic copy of the source when this could be obtained. The entry form includes all fields related directly to malaria prevalence, including some geographic descriptions (geographic extent of the study area, as well as the land cover type as reported by the author(s) as either urban or rural, and forest and/or rice cultivation), and a full description of the cross-sectional study and its results (number of surveys, parasite detection method, dates, age, range sampled, number of slides examined and numbers of positive individuals). Records of sibling species occurrence, where species were identified using molecular methods, were retrieved from the published literature (from both resistance and behavioural studies) and from unpublished sources to compile a set of presence records for each species. A larger dataset, including all Anopheles surveys in the region, was used as a background dataset that captured sampling bias. From Wiebe A, Longbottom J, Gleave K, Shearer FM, Sinka ME, Massey NC, Cameron E, Bhatt S, Gething PW, Hemingway J, Smith DL, Coleman M, Moyes CL. Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance. Malar J. 2017 Feb 20;16(1):85. doi: 10.1186/s12936-017-1734-y. PMID: 28219387; PMCID: PMC5319841. Once a relevant literature source was identified, information was extracted using a list of data fields specified by a detailed pro forma. Precise geo-positioning was conducted using established methods [39], so that any uncertainty associated with the positioning could be estimated [46–49]. From Hay SI, Sinka ME, Okara RM, Kabaria CW, Mbithi PM, Tago CC, Benz D, Gething PW, Howes RE, Patil AP, Temperley WH, Bangs MJ, Chareonviriyaphap T, Elyazar IR, Harbach RE, Hemingway J, Manguin S, Mbogo CM, Rubio-Palis Y, Godfray HC. Developing global maps of the dominant anopheles vectors of human malaria. PLoS Med. 2010 Feb 9;7(2):e1000209. doi: 10.1371/journal.pmed.1000209. References 39 Guerra CA, Hay SI, Lucioparedes LS, Gikandi PW, Tatem AJ, Noor AM, Snow RW. Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project. Malar J. 2007 Feb 16;6:17. doi: 10.1186/1475-2875-6-17. 46. Chapman AD, Wieczorek J (2006) Guide to best practices for georeferencing. Copenhagen: Global Biodiversity Information Facility. 47. Wieczorek J, Guo Q, Hijmans RJ (2004) The point-radius method for georeferencing locality descriptions and calculating associated uncertainty. Int J Geogr Inf Sci 18: 745–767. 48. Guralnick RP, Wieczorek J, Beaman R, Hijmans RJ (2006) BioGeomancer: automated georeferencing to map the world’s biodiversity data. PLoS Biol 4: e381. doi:10.1371/journal.pbio.0040381. 49. Guo Q, Liu Y, Wieczorek J (2008) Georeferencing locality descriptions and computing associated uncertainty using a probabilistic approach. Int J Geogr Inf Sci 22: 1067–1090. Marianne Sinka 0000-0001-7145-3179 principalInvestigator 2025-02-03T10:08:52.352+00:00 dataset Sinka M, Wiebe A (2025). Test publication of Malaria Atlas Project historical data. Version 1.3. Test Organization #1. Occurrence dataset. https://ipt.gbif.org/resource?r=map_historical_data_ii&v=1.3 1. Guerra CA, Hay SI, Lucioparedes LS, Gikandi PW, Tatem AJ, Noor AM, et al. Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project. Malar J. 2007;6:17. 2. Hay SI, Snow RW. The malaria Atlas Project: developing global maps of malaria risk. PLoS Med. 2006;(12):e473. 3. Hay SI, Sinka ME, Okara RM, Kabaria CW, Mbithi PM, Tago CC, et al. Developing Global Maps of the Dominant Anopheles Vectors of Human Malaria. PLoS Med [Internet]. 2010;7(2):e1000209. Available from: https://dx.plos.org/10.1371/journal.pmed.1000209 4. Sinka ME, Bangs MJ, Manguin S, Coetzee M, Mbogo CM, Hemingway J, et al. The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis. Parasites & Vectors. 2010;3(1):117. Available from: https://doi.org/10.1186/1756-3305-3-117 5. Sinka ME, Bangs MJ, Manguin S, Rubio-Palis Y, Chareonviriyaphap T, Coetzee M, et al. A global map of dominant malaria vectors. Parasites Vectors. 2012;5(1):69. Available from: https://parasitesandvectors.biomedcentral.com/articles/10.1186/1756-3305-5-69 6. Wiebe A, Longbottom J, Gleave K, Shearer FM, Sinka ME, Massey NC, et al. Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance. Malar J. 2017;16(1):85. c5a227d7-2259-44ea-88aa-b6e5252cbc35/v1.3.xml