Development and evaluation of a Markov model to predict changes in schistosomiasis prevalence in response to praziquantel treatment: a case study of Schistosoma mansoni in Uganda and Mali

Parasites and Vectors

Volumn 9, Issue 1, 2016, Pages 1-15

  Deol, Arminder ^a   Webster, Joanne P ^a,b   Walker, Martin ^a   Basáñez, Maria Gloria ^a   Hollingsworth, T Déirdre ^c   Fleming, Fiona M ^a   Montresor, Antonio ^d   French, Michael D ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b ROYAL VETERINARY COLLEGE   (United Kingdom)

^c UNIVERSITY OF WARWICK   (United Kingdom)

^d WORLD HEALTH ORGANIZATION   (Switzerland)

Author keywords

Intensity; Markov modelling; Praziquantel; Prevalence; Schistosomiasis; Transition probabilities; Transmission dynamics

Indexed keywords

PRAZIQUANTEL; ANTISCHISTOSOMAL AGENT;

ADOLESCENT; ARTICLE; CASE STUDY; CHILD; CONTROLLED STUDY; DISEASE SEVERITY; FOLLOW UP; GEOGRAPHIC DISTRIBUTION; HEALTH PROGRAM; HUMAN; MAJOR CLINICAL STUDY; MALI; MARKOV CHAIN; PARASITE CONTROL; PREDICTION; PREVALENCE; PROCESS DEVELOPMENT; SCHISTOSOMA MANSONI; SCHISTOSOMIASIS; UGANDA; ANIMAL; CROSS-SECTIONAL STUDY; DISEASE MANAGEMENT; DRUG EFFECTS; EVALUATION STUDY; PARASITOLOGY; SCHISTOSOMIASIS HAEMATOBIA; SCHISTOSOMIASIS MANSONI; SOFTWARE; STATISTICAL MODEL; TRANSMISSION;

ANIMALS; CROSS-SECTIONAL STUDIES; DISEASE MANAGEMENT; HUMANS; MALI; MARKOV CHAINS; MODELS, STATISTICAL; PRAZIQUANTEL; PREVALENCE; SCHISTOSOMA MANSONI; SCHISTOSOMIASIS HAEMATOBIA; SCHISTOSOMIASIS MANSONI; SCHISTOSOMICIDES; SOFTWARE; UGANDA;

EID: 84991694156     PISSN: None     EISSN: 17563305     Source Type: Journal    
DOI: 10.1186/s13071-016-1824-7     Document Type: Article

References (38)

1. Vos T, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2163-96.
2. WHO | Schistosomiasis. World Health Organization. Available from: http://www.who.int/schistosomiasis/en/. Accessed 10 Aug 2015
3. Hotez PJ. Forgotten people, forgotten diseases: the neglected tropical diseases and their impact on global health and development. ASM Press. 2011;2:41-55.
4. Assembly WH, Assembly T, Report P, Plan S, Region WHOA. WHO Weekly epidemiological record. 2014;21-8.
5. Global Schistosomiasis Alliance strives for elimination of the worm disease schistosomiasis. Available from: http://www.merck.de/company.merck.de/de/images/CRNews_2015_08_07_GSA_tcm1613_140462.pdf?Version=. Accessed 25 Jan 2015
6. Schistosomiasis Control Initiative | Imperial College London. Available from: https://www.imperial.ac.uk/schistosomiasis-control-initiative. Accessed 18 Sept 2015
7. Fighting schistosomiasis - Merck Sub-Saharan Africa. Available from: http://www.merckgroup.com/en/responsibility/living_our_commitment/schistosomiasis/schistosomiasis.html. Accessed 14 Sept 2015.
8. Fenwick A, Webster JP, Bosque-Oliva E, Blair L, Fleming FM, Zhang Y, et al. The Schistosomiasis Control Initiative (SCI): rationale, development and implementation from 2002-2008. Parasitol. 2009;136:1719-30.
9. WHO Progress report 2001-2011 and strategic plan 2012-2020. World Heal. Organ. 2013
10. Utzinger J, Keiser J. Schistosomiasis and soil-transmitted helminthiasis: common drugs for treatment and control. Expert Opin Pharmacother. 2004;5:263-85.
11. London Declaration on NTDs. Available from: http://unitingtocombatntds.org/resource/london-declaration. Accessed 14 Sept 2015
12. WHO
13. French MD, Churcher TS, Gambhir M, Fenwick A, Webster JP, Kabatereine NB, et al. Observed reductions in Schistosoma mansoni transmission from large-scale administration of praziquantel in Uganda: a mathematical modelling study. PLoS Negl Trop Dis. 2010;4:e897.
14. Touré S, Zhang Y, Bosqué-Oliva E, Ky C, Ouedraogo A, Koukounari A, et al. Two-year impact of single praziquantel treatment on infection in the national control programme on schistosomiasis in Burkina Faso. Bull World Health Organ. 2008;86:780-7.
15. Hodges MH, Dada N, Warmsley A, Paye J, Bangura MM, Nyorkor E, et al. Mass drug administration significantly reduces infection of Schistosoma mansoni and hookworm in school children in the national control program in Sierra Leone. BMC Infect Dis. 2012;12:16.
16. Montresor A, Gabrielli AF, Yajima A, Lethanh N, Biggs B-A, Casey GJ, et al. Markov model to forecast the change in prevalence of soil-transmitted helminths during a control programme: a case study in Vietnam. Trans R Soc Trop Med Hyg. 2013;107:313-8.
17. Montresor A, Deol A, À Porta N, Lethanh N, Jankovic D. Markov model predicts changes in STH prevalence during control activities even with a reduced amount of baseline information. PLoS Negl Trop Dis. 2016;10:e0004371.
18. Bishop YM, Light RJ, Mosteller F, Fienberg SE, Holland PW. Discrete multivariate analysis: theory and practice. Springer Science & Business Media; 2007
19. WHO Helminth control in school age children. Geneva: WHO Press; 2011.
20. WHO
21. Kabatereine N, Brooker S, Koukounari A, Kazibwe F, Tukahebwa EM, Fleming FM, et al. Impact of a national helminth control programme on infection and morbidity in Ugandan schoolchildren. Bull World Health Organ. 2007;85(2):91-9.
22. Zhang Y, Koukounari A, Kabatereine N, Fleming F, Kazibwe F, Tukahebwa E, et al. Parasitological impact of 2-year preventive chemotherapy on schistosomiasis and soil-transmitted helminthiasis in Uganda. BMC Med. 2007;5:27.
23. R Core Team. R
24. RStudio
25. Canty A, Ripley B. boot: Bootstrap R (S-Plus) Functions. R Packag. version 1.3-9. 2013.
26. Davison AC, Hinkley D V. Bootstrap methods and their applications. Cambridge Univ. Press;1997
27. Distribution of S. haematobium survey data in Uganda | Global Atlas of Helminth Infections. Available from: http://www.thiswormyworld.org/maps/2013/distribution-of-s-haematobium-survey-data-in-uganda. Accessed 22 Jun 2015
28. Siettos CI, Russo L. Mathematical modeling of infectious disease dynamics. Virulence. 2013;4:295-306.
29. Fulford AJ, Butterworth AE, Sturrock RF, Ouma JH. On the use of age-intensity data to detect immunity to parasitic infections, with special reference to Schistosoma mansoni in Kenya. Parasitology. 1992;105(Pt 2):219-27.
30. Kabatereine NB, Vennervald BJ, Ouma JH, Kemijumbi J, Butterworth AE, Dunne DW, et al. Adult resistance to schistosomiasis mansoni: age-dependence of reinfection remains constant in communities with diverse exposure patterns. Parasitology. 1999;118(Pt 1):101-5.
31. Fulford AJ, Butterworth AE, Ouma JH, Sturrock RF. A statistical approach to schistosome population dynamics and estimation of the life-span of Schistosoma mansoni in man. Parasitology. 2009;110:307.
32. Woolhouse MEJ. On the application of mathematical models of schistosome transmission dynamics. I. Natural transmission. Acta Trop. 1991;49:241-70.
33. Fulford AJ, Webster M, Ouma JH, Kimani G, Dunne DW. Puberty and Age-related changes in susceptibility to schistosome infection. Parasitol Today. 1998;14:23-6.
34. El-Khoby T, Galal N, Fenwick A, Barakat R, El-Hawey A, Nooman Z, et al. The epidemiology of schistosomiasis in Egypt: Summary findings in nine governorates. Am J Trop Med Hyg. 2000;62:88-99.
35. Anderson RM, May RM. Infectious diseases of humans: dynamics and control. Oxford: Oxford Science; 1991.
36. Rudge JW, Lu D-B, Fang G-R, Wang T-P, Basáñez M-G, Webster JP. Parasite genetic differentiation by habitat type and host species: molecular epidemiology of Schistosoma japonicum in hilly and marshland areas of Anhui Province, China. Mol Ecol. 2009;18:2134-47.
37. Webster JP, Gower CM, Knowles SCL, Molyneux DH, Fenton A. One Health - an ecological and evolutionary framework for tackling Neglected Zoonotic Diseases. Evol Appl. 2015;9:313-33.
38. Rudge JW, Webster JP, Lu D-B, Wang T-P, Fang G-R, Basanez MG. Identifying host species driving transmission of schistosomiasis japonica, a multihost parasite system, in China. Proc Natl Acad Sci USA. 2013;110:11457-62.