Volume 93, Issue 1
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645



Ethiopia has a diverse ecology and geography resulting in spatial and temporal variation in malaria transmission. Evidence-based strategies are thus needed to monitor transmission intensity and target interventions. A purposive selection of dried blood spots collected during cross-sectional school-based surveys in Oromia Regional State, Ethiopia, were tested for presence of antibodies against and antigens. Spatially explicit binomial models of seroprevalence were created for each species using a Bayesian framework, and used to predict seroprevalence at 5 km resolution across Oromia. School seroprevalence showed a wider prevalence range than microscopy for both (0–50% versus 0–12.7%) and (0–53.7% versus 0–4.5%), respectively. The model incorporated environmental predictors and spatial random effects, while seroprevalence first-order trends were not adequately explained by environmental variables, and a spatial smoothing model was developed. This is the first demonstration of serological indicators being used to detect large-scale heterogeneity in malaria transmission using samples from cross-sectional school-based surveys. The findings support the incorporation of serological indicators into periodic large-scale surveillance such as Malaria Indicator Surveys, and with particular utility for low transmission and elimination settings.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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  1. World Health Organization, 2012. Disease Surveillance for Malaria Elimination. Available at: http://whqlibdoc.who.int/publications/2012/9789241503334_eng.pdf. Accessed November 4, 2013. [Google Scholar]
  2. Greenwood BM, , 2008. Control to elimination: implications for malaria research. Trends Parasitol 24: 449454.[Crossref] [Google Scholar]
  3. Cotter C, Sturrock HJ, Hsiang MS, Liu J, Phillips AA, Hwang J, Gueye CS, Fullman N, Gosling RD, Feachem RG, , 2013. The changing epidemiology of malaria elimination: new strategies for new challenges. Lancet 382: 900911.[Crossref] [Google Scholar]
  4. Tatem AJ, Smith DL, Gething PW, Kabaria CW, Snow RW, Hay SI, , 2010. Ranking of elimination feasibility between malaria-endemic countries. Lancet 376: 15791591.[Crossref] [Google Scholar]
  5. Okell LC, Bousema T, Griffin JT, Ouedraogo AL, Ghani AC, Drakeley CJ, , 2012. Factors determining the occurrence of submicroscopic malaria infections and their relevance for control. Nat Commun 3: 1237.[Crossref] [Google Scholar]
  6. Ishengoma DS, Francis F, Mmbando BP, Lusingu JP, Magistrado P, Alifrangis M, Theander TG, Bygbjerg IC, Lemnge MM, , 2011. Accuracy of malaria rapid diagnostic tests in community studies and their impact on treatment of malaria in an area with declining malaria burden in north-eastern Tanzania. Malar J 10: 176.[Crossref] [Google Scholar]
  7. Littrell M, Sow GD, Ngom A, Ba M, Mboup BM, Dieye Y, Mutombo B, Earle D, Steketee RW, , 2013. Case investigation and reactive case detection for malaria elimination in northern Senegal. Malar J 12: 331.[Crossref] [Google Scholar]
  8. Searle KM, Shields T, Hamapumbu H, Kobayashi T, Mharakurwa S, Thuma PE, Smith DL, Glass G, Moss WJ, , 2013. Efficiency of household reactive case detection for malaria in rural southern Zambia: simulations based on cross-sectional surveys from two epidemiological settings. PLoS ONE 8: e70972.[Crossref] [Google Scholar]
  9. Sturrock HJ, Novotny JM, Kunene S, Dlamini S, Zulu Z, Cohen JM, Hsiang MS, Greenhouse B, Gosling RD, , 2013. Reactive case detection for malaria elimination: real-life experience from an ongoing program in Swaziland. PLoS ONE 8: e63830.[Crossref] [Google Scholar]
  10. Roca-Feltrer A, Lalloo DG, Phiri K, Terlouw DJ, , 2012. Rolling Malaria Indicator Surveys (rMIS): a potential district-level malaria monitoring and evaluation (M&E) tool for program managers. Am J Trop Med Hyg 86: 9698.[Crossref] [Google Scholar]
  11. Corran P, Coleman P, Riley E, Drakeley C, , 2007. Serology: a robust indicator of malaria transmission intensity? Trends Parasitol 23: 575582.[Crossref] [Google Scholar]
  12. Corran PH, Cook J, Lynch C, Leendertse H, Manjurano A, Griffin J, Cox J, Abeku T, Bousema T, Ghani AC, Drakeley C, Riley E, , 2008. Dried blood spots as a source of anti-malarial antibodies for epidemiological studies. Malar J 7: 195.[Crossref] [Google Scholar]
  13. Stewart L, Gosling R, Griffin J, Gesase S, Campo J, Hashim R, Masika P, Mosha J, Bousema T, Shekalaghe S, Cook J, Corran P, Ghani A, Riley EM, Drakeley C, , 2009. Rapid assessment of malaria transmission using age-specific sero-conversion rates. PLoS ONE 4: e6083.[Crossref] [Google Scholar]
  14. Drakeley CJ, Corran PH, Coleman PG, Tongren JE, McDonald SLR, Carneiro I, Malima R, Lusingu J, Manjurano A, Nkya WMM, Lemnge MM, Cox J, Reyburn H, Riley EM, , 2005. Estimating medium- and long-term trends in malaria transmission by using serological markers of malaria exposure. Proc Natl Acad Sci USA 102: 51085113.[Crossref] [Google Scholar]
  15. Bousema T, Youssef RM, Cook J, Cox J, Alegana VA, Amran J, Noor AM, Snow RW, Drakeley C, , 2010. Serologic markers for detecting malaria in areas of low endemicity, Somalia, 2008. Emerg Infect Dis 16: 392399.[Crossref] [Google Scholar]
  16. Oduro AR, Conway DJ, Schellenberg D, Satoguina J, Greenwood BM, Bojang KA, , 2013. Seroepidemiological and parasitological evaluation of the heterogeneity of malaria infection in the Gambia. Malar J 12: 222.[Crossref] [Google Scholar]
  17. Satoguina J, Walther B, Drakeley C, Nwakanma D, Oriero EC, Correa S, Corran P, Conway DJ, Walther M, , 2009. Comparison of surveillance methods applied to a situation of low malaria prevalence at rural sites in The Gambia and Guinea Bissau. Malar J 8: 274.[Crossref] [Google Scholar]
  18. Hsiang MS, Hwang J, Kunene S, Drakeley C, Kandula D, Novotny J, Parizo J, Jensen T, Tong M, Kemere J, Dlamini S, Moonen B, Angov E, Dutta S, Ockenhouse C, Dorsey G, Greenhouse B, , 2012. Surveillance for malaria elimination in Swaziland: a national cross-sectional study using pooled PCR and serology. PLoS ONE 7: e29550.[Crossref] [Google Scholar]
  19. Noor AM, Mohamed MB, Mugyenyi CK, Osman MA, Guessod HH, Kabaria CW, Ahmed IA, Nyonda M, Cook J, Drakeley CJ, Mackinnon MJ, Snow RW, , 2011. Establishing the extent of malaria transmission and challenges facing pre-elimination in the Republic of Djibouti. BMC Infect Dis 11: 121.[Crossref] [Google Scholar]
  20. Brooker S, Kolaczinski J, Gitonga C, Noor A, Snow R, , 2009. The use of schools for malaria surveillance and programme evaluation in Africa. Malar J 8: 231.[Crossref] [Google Scholar]
  21. Gitonga CW, Karanja PN, Kihara J, Mwanje M, Juma E, Snow RW, Noor AM, Brooker S, , 2010. Implementing school malaria surveys in Kenya: towards a national surveillance system. Malar J 9: 306.[Crossref] [Google Scholar]
  22. Gitonga CW, Kihara JH, Njenga SM, Awuondo K, Noor AM, Snow RW, Brooker SJ, , 2012. Use of rapid diagnostic tests in malaria school surveys in Kenya: does their under-performance matter for planning malaria control? Am J Trop Med Hyg 87: 10041011.[Crossref] [Google Scholar]
  23. Stevenson JC, Stresman GH, Gitonga CW, Gillig J, Owaga C, Marube E, Odongo W, Okoth A, China P, Oriango R, Brooker SJ, Bousema T, Drakeley C, Cox J, , 2013. Reliability of school surveys in estimating geographic variation in malaria transmission in the western Kenyan highlands. PLoS ONE 8: e77641.[Crossref] [Google Scholar]
  24. Ghebreyesus TA, Haile M, Witten KH, Getachew A, Yohannes AM, Yohannes M, Teklehaimanot HD, Lindsay SW, Byass P, , 1999. Incidence of malaria among children living near dams in northern Ethiopia: community based incidence survey. BMJ 319: 663666.[Crossref] [Google Scholar]
  25. Abeku T, Van Oortmarssen GJ, Borsboom G, De Vlas SJ, Habbema JDF, , 2003. Spatial and temporal variations of malaria epidemic risk in Ethiopia: factors involved and implications. Acta Trop 87: 331340.[Crossref] [Google Scholar]
  26. Lautze J, McCartney M, Kirshen P, Olana D, Jayasinghe G, Spielman A, , 2007. Effect of a large dam on malaria risk: the Koka reservoir in Ethiopia. Trop Med Int Health 12: 982989.[Crossref] [Google Scholar]
  27. Midekisa A, Senay G, Henebry GM, Semuniguse P, Wimberly MC, , 2012. Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia. Malar J 11: 165.[Crossref] [Google Scholar]
  28. Graves PM, Richards FO, Ngondi J, Emerson PM, Shargie EB, Endeshaw T, Ceccato P, Ejigsemahu Y, Mosher AW, Hailemariam A, Zerihun M, Teferi T, Ayele B, Mesele A, Yohannes G, Tilahun A, Gebre T, , 2009. Individual, household and environmental risk factors for malaria infection in Amhara, Oromia and SNNP regions of Ethiopia. Trans R Soc Trop Med Hyg 103: 12111220.[Crossref] [Google Scholar]
  29. The Ethiopian Health and Nutrition Research Institute and partners, 2012. Ethiopia National Malaria Indicator Survey 2011. Addis Ababa, Ethiopia: Federal Ministry of Health. [Google Scholar]
  30. Ashton RA, Kefyalew T, Tesfaye G, Pullan RL, Yadeta D, Reithinger R, Kolaczinski JH, Brooker S, , 2011. School-based surveys of malaria in Oromia Regional State, Ethiopia: a rapid survey method for malaria in low transmission settings. Malar J 10: 25.[Crossref] [Google Scholar]
  31. World Health Organization, 2001. Iron Deficiency Anaemia: Assessment, Prevention and Control. A Guide for Programme Managers. Geneva, Switzerland: World Health Organization. [Google Scholar]
  32. Bousema T, Drakeley C, Gesase S, Hashim R, Magesa S, Mosha F, Otieno S, Carneiro I, Cox J, Msuya E, Kleinschmidt I, Maxwell C, Greenwood B, Riley E, Sauerwein R, Chandramohan D, Gosling R, , 2010. Identification of hot spots of malaria transmission for targeted malaria control. J Infect Dis 201: 17641774.[Crossref] [Google Scholar]
  33. Cook J, Kleinschmidt I, Schwabe C, Nseng G, Bousema T, Corran PH, Riley EM, Drakeley CJ, , 2011. Serological markers suggest heterogeneity of effectiveness of malaria control interventions on Bioko Island, Equatorial Guinea. PLoS ONE 6: e25137.[Crossref] [Google Scholar]
  34. Cook J, Reid H, Iavro J, Kuwahata M, Taleo G, Clements A, McCarthy J, Vallely A, Drakeley C, , 2010. Using serological measures to monitor changes in malaria transmission in Vanuatu. Malar J 9: 169.[Crossref] [Google Scholar]
  35. USGS-SRTM. Shuttle Radar Topography Mission Digital Elevation Model. Available at: http://srtm.csi.cgiar.org. Accessed November 4, 2013. [Google Scholar]
  36. WorldClim. WorldClim Global Climate Data. Available at: http://www.worldclim.org. Accessed November 4, 2013. [Google Scholar]
  37. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, , 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25: 19651978.[Crossref] [Google Scholar]
  38. USGS. SRTM Water Bodies Data Files. Available at: https://lta.cr.usgs.gov/srtm_water_body_dataset. Accessed November 4, 2013. [Google Scholar]
  39. Digital Chart of the World. Available at: http://diva-gis.org/gdata. Accessed November 4, 2013.
  40. Matsuoka H, Nguon C, Kanbe T, Jalloh A, Sato H, Yoshida S, Hirai M, Arai M, Socheat D, Kawamoto F, , 2005. Glucose-6-phosphate dehydrogenase (G6PD) mutations in Cambodia: G6PD Viangchan (871G > A) is the most common variant in the Cambodian population. J Hum Genet 50: 468472.[Crossref] [Google Scholar]
  41. SPOT Vegetation. Spot 5 Vegetation. Available at: http://www.spot-vegetation.com. Accessed November 4, 2013. [Google Scholar]
  42. WorldPop Project. Available at: http://www.worldpop.org.uk/. Accessed November 4, 2013.
  43. SEDAC. Global Rural-Urban Mapping Project (GRUMP), v1. Available at: http://sedac.ciesin.columbia.edu/data/collection/grump-v1. Accessed November 4, 2013. [Google Scholar]
  44. Schwarz G, , 1978. Estimating the dimensions of a model. Ann Stat 6: 461464.[Crossref] [Google Scholar]
  45. Akaike H, Petrov BN, Caski F, , 1973. Information theory and an extension of the maximum likelihood principle. , ed. Proceeding of the Second International Symposium on Information Theory. Budapest, Hungary: Akademiai Kiado, 276281. [Google Scholar]
  46. Diggle PJ, Ribeiro PJJ, , 2007. Model-Based Geostatistics. New York, NY: Springer. [Google Scholar]
  47. Spiegelhalter DJ, Best NG, Carlin BR, van der Linde A, , 2002. Bayesian measures of model complexity and fit. J R Stat Soc, B 64: 583616.[Crossref] [Google Scholar]
  48. Swets JA, , 1988. Measuring the accuracy of diagnostic systems. Science 240: 12851293.[Crossref] [Google Scholar]
  49. Clements ACA, Lwambo NJS, Blair L, Nyandindi U, Kaatano G, Kinung'hi S, Webster JP, Fenwick A, Brooker S, , 2006. Bayesian spatial analysis and disease mapping: tools to enhance planning and implementation of a schistosomiasis control programme in Tanzania. Trop Med Int Health 11: 490503.[Crossref] [Google Scholar]
  50. Fawcett T, , 2006. An introduction to ROC analysis. Pattern Recognit Lett 27: 861874.[Crossref] [Google Scholar]
  51. Federal Democratic Republic of Ethiopia MoH, 2012. National Malaria Guidelines, 3rd Ed. Addis Ababa, Ethiopia: Ministry of Health (MoH). [Google Scholar]
  52. Reid HL, Haque U, Roy S, Islam N, Clements AC, , 2012. Characterizing the spatial and temporal variation of malaria incidence in Bangladesh, 2007. Malar J 11: 170.[Crossref] [Google Scholar]
  53. Guerra CA, Howes RE, Patil AP, Gething PW, Van Boeckel TP, Temperley WH, Kabaria CW, Tatem AJ, Manh BH, Elyazar IRF, Baird JK, Snow RW, Hay SI, , 2010. The international limits and population at risk of Plasmodium vivax transmission in 2009. PLoS Negl Trop Dis 4: e774.[Crossref] [Google Scholar]
  54. Gething PW, Patil AP, Smith DL, Guerra CA, Elyazar IRF, Johnston GL, Tatem AJ, Hay SI, , 2011. A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J 10: 378.[Crossref] [Google Scholar]
  55. Malaria Atlas Project, 2013. Malaria Atlas Project Maps of Malaria Risk in Ethiopia. Available at: http://www.map.ox.ac.uk/explore/countries/ETH. Accessed September 23, 2013. [Google Scholar]
  56. Diggle PJ, Menezes R, Su T, , 2010. Geostatistical inference under preferential sampling. Appl Stat 59: 191232. [Google Scholar]
  57. Hartgers FC, Yazdanbakhsh M, , 2006. Co-infection of helminths and malaria: modulation of the immune responses to malaria. Parasite Immunol 28: 497506.[Crossref] [Google Scholar]
  58. Garrett-Jones C, Shidrawi GR, , 1969. Malaria vectorial capacity of a population of Anopheles gambiae: an exercise in epidemiological entomology. Bull World Health Organ 40: 531545. [Google Scholar]
  59. Poncon N, Tran A, Toty C, Luty AJ, Fontenille D, , 2008. A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France. Malar J 7: 147.[Crossref] [Google Scholar]
  60. Oidtmann B, Peeler E, Lyngstad T, Brun E, Bang Jensen B, Stark KD, , 2013. Risk-based methods for fish and terrestrial animal disease surveillance. Prev Vet Med 112: 1326.[Crossref] [Google Scholar]
  61. Rodriguez-Prieto V, Vicente-Rubiano M, Sanchez-Matamoros A, Rubio-Guerri C, Melero M, Martinez-Lopez B, Martinez-Aviles M, Hoinville L, Vergne T, Comin A, Schauer B, Dorea F, Pfeiffer DU, Sanchez-Vizcaino JM, , 2014. Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations. Epidemiol Infect 12: 125. [Google Scholar]

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  • Received : 05 Oct 2014
  • Accepted : 25 Feb 2015
  • Published online : 08 Jul 2015

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