CoChat
Sign Up
Cited by 12

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Côte d’Ivoire

Houngbedji, Clarisse A., Chammartin, Frédérique, Yapi, Richard B., Hürlimann, Eveline, N’Dri, Prisca B., Silué, Kigbafori D., Soro, Gotianwa, Koudou, Benjamin G., Assi, Serge-Brice, N’Goran, Eliézer K., Fantodji, Agathe, Utzinger, Jürg, Vounatsou, Penelope, Raso, Giovanna·2016·Parasites & Vectors
DOI 10.1186/s13071-016-1775-zPMC PMC5015250
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13071-016-1775-z

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Modelled PfPR maps are developed by assembling community-based PfPR data from the general population or specific population surveys and used within geostatistical models to provide estimates of infection prevalence at unsampled locations.

    “Modelled PfPR maps are developed by assembling community-based malaria parasite prevalence (PfPR) data from the general population or specific population surveys, such as school based children [12–16], and used within geostatistical models to provide estimates of infection prevalence at unsampled locations [17].”

    From How useful are malaria risk maps at the country level? Perceptions of decision-makers in Kenya, Malawi and the Democratic Republic of Congo (2020) · cites this paper as [15]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 43

  1. WHO. World Malaria Report. Geneva: World Health Organization; 2015.
  2. Vos T, Barber RM, Bell B, Bertozzi-Villa A, Biryukov S, Bolliger I, Charlson F, Davis A, Degenhardt L, Dicker D, Duan L, Erskine H, Feigin VL, Ferrari AJ,Fitzmaurice C, Fleming T, Graetz N, Guinovart C, Haagsma J, Hansen GM, Hanson SW, Heuton KR, Higashi H, Kassebaum N, Kyu H, Laurie E, Liang X, Lofgren K, Lozano R, MacIntyre MF, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease study 2013. Lancet. 2015;386:743–800. · DOI · Paper page
  3. Sachs J, Malaney P. The economic and social burden of malaria. Nature. 2002;415:680–5. · DOI · Paper page
  4. Chima RI, Goodman CA, Mills A. The economic impact of malaria in Africa: a critical review of the evidence. Health Policy. 2003;63:17–36. · DOI
  5. Guinovart C, Navia MM, Tanner M, Alonso PL. Malaria: burden of disease. Curr Mol Med. 2006;6:137–40. · DOI
  6. Bhatt S, Weiss DJ, Cameron E, Bisanzio D, Mappin B, Dalrymple U, Battle KE, Moyes CL, Henry A, Eckhoff PA, Wenger EA, Briët O, Penny MA, Smith TA, Bennett A, Yukich J, Eisele TP, Griffin JT, Fergus CA, Lynch M, Lindgren F, Cohen JM, Murray CLJ, Smith DL, Hay SI, Cibulskis RE, Gething PW. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526:207–11. · DOI · Paper page
  7. Hay SI, Snow RW. The Malaria Atlas Project: developing global maps of malaria risk. PLoS Med. 2006;3:e473. · DOI
  8. Giardina F, Kasasa S, Sié A, Utzinger J, Tanner M, Vounatsou P. Effects of vector-control interventions on changes in risk of malaria parasitaemia in sub-Saharan Africa: a spatial and temporal analysis. Lancet Glob Health. 2014;2:e601–615. · DOI
  9. Hay SI, Snow RW, Rogers DJ. From predicting mosquito habitat to malaria seasons using remotely sensed data: practice, problems and perspectives. Parasitol Today. 1998;14:306–13. · DOI
  10. Rogers DJ, Randolph SE, Snow RW, Hay SI. Satellite imagery in the study and forecast of malaria. Nature. 2002;415:710–5. · DOI
  11. Kalluri S, Gilruth P, Rogers D, Szczur M. Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review. PLoS Pathog. 2007;3:e116. · DOI
  12. Vounatsou P, Raso G, Tanner M, N'Goran EK, Utzinger J. Bayesian geostatistical modelling for mapping schistosomiasis transmission. Parasitology. 2009;136:1695–705. · DOI
  13. Beck LR, Rodriguez MH, Dister SW, Rodriguez AD, Rejmankova E, Ulloa A, Meza RA, Roberts DR, Paris JF, Spanner MA, Washino RK, Hacker C, Legters LJ. Remote sensing as a landscape epidemiologic tool to identify villages at high risk for malaria transmission. Am J Trop Med Hyg. 1994;51:271–80. · DOI
  14. Hay SI, Snow RW, Rogers DJ. Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Trans R Soc Trop Med Hyg. 1998;92:12–20. · DOI
  15. Lindsay SW, Parson L, Thomas CJ. Mapping the ranges and relative abundance of the two principal African malaria vectors, Anopheles gambiae sensu stricto and An. arabiensis, using climate data. Proc R Soc Lond B. 1998;265:847–54. · DOI
  16. Jeanne I. Paludisme et schistosome: deux exemples d'utilisation des systèmes d'information géographique et de la télédétection à Madagascar. Bull Soc Pathol Exot. 2000;93:208–14.
  17. Brooker S, Leslie T, Kolaczinski K, Mohsen E, Mehboob N, Saleheen S, Khudonazarov J, Freeman T, Clements A, Rowland M, Kolaczinski J. Spatial epidemiology of Plasmodium vivax, Afghanistan. Emerg Infect Dis. 2006;12:1600–2. · DOI
  18. Kleinschmidt I, Bagayoko M, Clarke GPY, Craig M, Le Sueur D. A spatial statistical approach to malaria mapping. Int J Epidemiol. 2000;29:355–61. · DOI
  19. Gosoniu L, Vounatsou P, Sogoba N, Maire N, Smith T. Mapping malaria risk in West Africa using a Bayesian nonparametric non-stationary model. Comput Stat Data Anal. 2009;53:3358–71. · DOI
  20. Silué KD, Raso G, Yapi A, Vounatsou P, Tanner M, N’Goran EK, Utzinger J. Spatially-explicit risk profiling of Plasmodium falciparum infections at a small scale: a geostatistical modelling approach. Malar J. 2008;7:111. · DOI
  21. Raso G, Silué KD, Vounatsou P, Singer BH, Yapi A, Tanner M, Utzinger J, N’Goran EK. Spatial risk profiling of Plasmodium falciparum parasitaemia in a high endemicity area in Côte d'Ivoire. Malar J. 2009;8:252. · DOI
  22. Gosoniu L, Vounatsou P, Sogoba N, Smith T. Bayesian modelling of geostaitistical malaria risk data. Geospat Health. 2006;1:127–39. · DOI · Paper page
  23. Mabaso MLH, Vounatsou P, Midzi S, Da Silva J, Smith T. Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incdence in Zimbabwe. Int J Health Geograph. 2006;5:20. · DOI
  24. Sogoba N, Vounatsou P, Doumbia S, Bagayoko M, Touré MB, Sissoko IM, Traore SF, Touré YT, Smith T. Spatial analysis of malaria transmission parameters in the rice cultivation area of office du Niger, Mali. Am J Trop Med Hyg. 2007;76:1009–15. · DOI
  25. Hay SI, Guerra CA, Gething PW, Patil AP, Tatem AJ, Noor AM, Kabaria CW, Manh BH, Elyazar IRF, Brooker S, Smith DL, Moyeed RA, Snow RW. A world malaria map: Plasmodium falciparum endemicity in 2007. PLoS Med. 2009;6:e1000048. · DOI
  26. Gething PW, Patil AP, Smith DL, Guerra CA, Elyazar IRF, Johnston GL, Tatem AJ, Hay SI. A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J. 2011;10:378. · DOI
  27. Yapi RB, Hürlimann E, Houngbedji CA, N’Dri PB, Silué KD, Soro G, Kouamé FN, Vounatsou P, Fürst T, N’Goran EK, Utzinger J, Raso G. Infection and co-infection with helminths and Plasmodium among school children in Côte d’Ivoire: results from a national cross-sectional survey. PLoS Negl Trop Dis. 2014;8:e2913. · DOI
  28. Houngbedji CA, N’Dri PB, Hürlimann E, Yapi RB, Silué KD, Soro G, Koudou BG, Acka CA, Assi S-B, Vounatsou P, N’Goran EK, Fantodji A, Utzinger J, Raso G. Disparities of Plasmodium falciparum infection, malaria-related morbidity and access to malaria prevention and treatment among school-aged children: a national cross-sectional survey in Côte d’Ivoire. Malar J. 2015;14:7. · DOI
  29. Hürlimann E, Houngbedji CA, Yapi RB, N’Dri PB, Silué KD, Soro G, Kouamé FN, Fürst T, Utzinger J, N’Goran EK, Raso G. Health-related quality of life among school children with parasitic infections: findings from a national cross-sectional survey in Côte d’Ivoire. PLoS Negl Trop Dis. 2014;8:e3287. · DOI
  30. Diggle PJ, Tawn JA, Moyeed RA. Model-based geostatistics. J R Stat Soc Ser C Appl Stat. 1998;47:299–326. · DOI
  31. Montresor A, Crompton DWT, Gyorkos TW, Savioli L. Helminth control in school-age children: a guide for managers of control programmes in planning. Geneva: World Health Organization; 2002.
  32. Chammartin F, Scholte RGC, Malone JB, Bavia ME, Nieto P, Utzinger J, Vounatsou P. Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia. Parasit Vectors. 2013;6:152. · DOI
  33. Scheipl F, Fahrmeir L, Kneib T. Spike-and-slab priors for function selection in structured additive regression models. J Am Stat Assoc. 2012;107:1518–32. · DOI
  34. Cressie N. The origins of kriging. Math Geol. 1990;22:239–52. · DOI
  35. Krefis AC, Schwarz NG, Nkrumah B, Acquah S, Loag W, Oldeland J, Sarpong N, Adu-Sarkodie Y, Ranft U, May J. Spatial analysis of land cover determinants of malaria incidence in the Ashanti region, Ghana. PLoS One. 2011;6:e17905. · DOI
  36. Brooker S, Clarke S, Njagi JK, Polack S, Mugo B, Estambale B, Muchiri E, Magnussen P, Cox J. Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of western Kenya. Trop Med Int Health. 2004;9:757–66. · DOI · Paper page
  37. Gallup JL, Sachs JD. The economic burden of malaria. Am J Trop Med Hyg. 2001;64:85–96. · DOI
  38. Worrall E, Basu S, Hanson K. Is malaria a disease of poverty? A review of the literature. Trop Med Int Health. 2005;10:1047–59. · DOI
  39. Utzinger J, Keiser J. Urbanisation and tropical health - then and now. Ann Trop Med Parasitol. 2006;100:517–33. · DOI
  40. Doannio JMC, Dossou-Yovo J, Diarrassouba S, Rakotondraibé ME, Chauvancy G, Chandre F, Rivière F, Carnevale P. La dynamique de la transmission du paludisme à Kafiné, un village rizicole en zone de savane humide de Côte d’Ivoire. Bull Soc Pathol Exot. 2002;95:11–6.
  41. Nzeyimana I, Henry M-C, Dossou-Yovo J, Doannio JMC, Diawara L, Carnevale P. Épidémiologie du paludisme dans le sud-ouest forestier de la Côte d’Ivoire (région de Taï). Bull Soc Pathol Exot. 2002;95:89–94.
  42. Chammartin F, Hürlimann E, Raso G, N’Goran EK, Utzinger J, Vounatsou P. Statistical methodological issues in mapping historical schistosomiasis survey data. Acta Trop. 2013;128:345–52. · DOI
  43. WHO. Guidelines for the treatment of malaria. Geneva: World Health Organization; 2006.

Cited by

Sorted by citations

Metadata

Authors
Houngbedji, C. A., Chammartin, F., Yapi, R. B., Hürlimann, E., N’Dri, P. B., Silué, K. D., Soro, G., Koudou, B. G., Assi, S.-B., N’Goran, E. K., Fantodji, A., Utzinger, J., Vounatsou, P., & Raso, G.
Venue
Parasites & Vectors
Publisher
Springer Science and Business Media LLC
Published
2016-09-07
Volume
9
Issue
1
ISSN
1756-3305
DOI
10.1186/s13071-016-1775-z
PMC
PMC5015250
Cited by
12
References
4
Language
en
Funders
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (32003B-132949, IZ70Z0_123900)
  • PASRES (47_2009)
  • European Research Council (3231805-IMCCA)
  • Swiss Programme for Research on Global Issues for Development (IZ01Z0-147286)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review