Background Morbidity due to Schistosoma haematobium and hookworm infections is marked in those with intense co-infections by these parasites. The development of a spatial predictive decision-support tool is crucial for targeting the delivery of integrated mass drug administration (MDA) to those most in need. We investigated the co-distribution of S. haematobium and hookworm infection, plus the spatial overlap of infection intensity of both parasites, in Ghana. The aim was to produce maps to assist the planning and evaluation of national parasitic disease control programs. Methodology/Principal Findings A national cross-sectional school-based parasitological survey was conducted in Ghana in 2008, using standardized sampling and parasitological methods. Bayesian geostatistical models were built, including a multinomial regression model for S. haematobium and hookworm mono- and co-infections and zero-inflated Poisson regression models for S. haematobium and hookworm infection intensity as measured by egg counts in urine and stool respectively. The resulting infection intensity maps were overlaid to determine the extent of geographical overlap of S. haematobium and hookworm infection intensity. In Ghana, prevalence of S. haematobium mono-infection was 14.4%, hookworm mono-infection was 3.2%, and S. haematobium and hookworm co-infection was 0.7%. Distance to water bodies was negatively associated with S. haematobium and hookworm co-infections, hookworm mono-infections and S. haematobium infection intensity. Land surface temperature was positively associated with hookworm mono-infections and S. haematobium infection intensity. While high-risk (prevalence >10–20%) of co-infection was predicted in an area around Lake Volta, co-intensity was predicted to be highest in foci within that area. Conclusions/Significance Our approach, based on the combination of co-infection and co-intensity maps allows the identification of communities at increased risk of severe morbidity and environmental contamination and provides a platform to evaluate progress of control efforts.
References
[1]
Hotez PJ, Molyneux DH, Fenwick A, Kumaresan J, Sachs SE, et al. (2007) Control of neglected tropical diseases. N Engl J Med 357: 1018–1027. doi: 10.1056/NEJMra064142
[2]
Hotez P (2008) Hookworm and poverty. Ann N Y Acad Sci 1136: 38–44. doi: 10.1196/annals.1425.000
[3]
Brooker S, Clements AC (2009) Spatial heterogeneity of parasite co-infection: Determinants and geostatistical prediction at regional scales. Int J Parasitol 39: 591–597. doi: 10.1016/j.ijpara.2008.10.014
[4]
Steinmann P, Keiser J, Bos R, Tanner M, Utzinger J (2006) Schistosomiasis and water resources development: systematic review, meta-analysis, and estimates of people at risk. Lancet Infect Dis 6: 411–425. doi: 10.1016/S1473-3099(06)70521-7
[5]
Howard SC, Donnelly CA, Kabatereine NB, Ratard RC, Brooker S (2002) Spatial and intensity-dependent variations in associations between multiple species helminth infections. Acta Trop 83: 141–149. doi: 10.1016/S0001-706X(02)00093-1
[6]
Booth M, Bundy DA, Albonico M, Chwaya HM, Alawi KS, et al. (1998) Associations among multiple geohelminth species infections in schoolchildren from Pemba Island. Parasitology 116(Pt 1): 85–93. doi: 10.1017/S003118209700190X
[7]
Pullan R, Brooker S (2008) The health impact of polyparasitism in humans: are we under-estimating the burden of parasitic diseases? Parasitology 135: 783–794. doi: 10.1017/S0031182008000346
[8]
Molyneux DH, Hotez PJ, Fenwick A (2005) “Rapid-impact interventions”: how a policy of integrated control for Africa's neglected tropical diseases could benefit the poor. PLoS Med 2: e336. doi: 10.1371/journal.pmed.0020336
[9]
Fenwick A, Webster JP, Bosque-Oliva E, Blair L, Fleming FM, et al. (2009) The Schistosomiasis Control Initiative (SCI): rationale, development and implementation from 2002–2008. Parasitology 136: 1719–1730. doi: 10.1017/S0031182009990400
[10]
Kotze AC, Kopp SR (2008) The potential impact of density dependent fecundity on the use of the faecal egg count reduction test for detecting drug resistance in human hookworms. PLoS Negl Trop Dis 2: e297. doi: 10.1371/journal.pntd.0000297
[11]
Churcher TS, Filipe JA, Basá？ez MG (2006) Density dependence and the control of helminth parasites. J Anim Ecol 75: 1313–1320. doi: 10.1111/j.1365-2656.2006.01154.x
[12]
Clements AC, Brooker S, Nyandindi U, Fenwick A, Blair L (2008) Bayesian spatial analysis of a national urinary schistosomiasis questionnaire to assist geographic targeting of schistosomiasis control in Tanzania, East Africa. Int J Parasitol 38: 401–415. doi: 10.1016/j.ijpara.2007.08.001
[13]
Clements AC, Firth S, Dembele R, Garba A, Toure A, et al. (2010) Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in West Africa. Bulletin of the World Health Organization 87: 921–929. doi: 10.2471/BLT.08.058933
[14]
Clements AC, Garba A, Sacko M, Toure S, Dembele R, et al. (2008) Mapping the probability of schistosomiasis and associated uncertainty, West Africa. Emerg Infect Dis 14: 1629–1632. doi: 10.3201/eid1410.080366
[15]
Clements AC, Lwambo NJ, Blair L, Nyandindi U, Kaatano G, et al. (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: 490–503. doi: 10.1111/j.1365-3156.2006.01594.x
[16]
Diggle PJ, Thomson MC, Christensen OF, Rowlingson B, Obsomer V, et al. (2007) Spatial modelling and the prediction of Loa loa risk: decision making under uncertainty. Ann Trop Med Parasitol 101: 499–509. doi: 10.1179/136485907X229121
[17]
Magalh？es RJ, Clements AC, Patil AP, Gething PW, Brooker S (2011) The applications of model-based geostatistics in helminth epidemiology and control. Adv Parasitol 74: 267–296. doi: 10.1016/B978-0-12-385897-9.00005-7
[18]
Brooker S, Clements AC, Hotez PJ, Hay SI, Tatem AJ, et al. (2006) The co-distribution of Plasmodium falciparum and hookworm among African schoolchildren. Malar J 5: 99. doi: 10.1186/1475-2875-5-99
[19]
Raso G, Vounatsou P, Singer BH, N'Goran EK, Tanner M, et al. (2006) An integrated approach for risk profiling and spatial prediction of Schistosoma mansoni-hookworm coinfection. Proc Natl Acad Sci U S A 103: 6934–6939. doi: 10.1073/pnas.0601559103
[20]
Clements AC, Moyeed R, Brooker S (2006) Bayesian geostatistical prediction of the intensity of infection with Schistosoma mansoni in East Africa. Parasitology 133: 711–719. doi: 10.1017/S0031182006001181
Garba A, Touré S, Dembele R, Boisier P, Tohon Z, et al. (2009) Present and future schistosomiasis control activities with support from the Schistosomiasis Control Initiative in West Africa. Parasitology 136: 1731–1737. doi: 10.1017/S0031182009990369
[23]
Clements AC, Bosqué-Oliva E, Sacko M, Landoure A, Dembele R, et al. (2009) A comparative study of the spatial distribution of schistosomiasis in mali in 1984–1989 and 2004–2006. PLoS Negl Trop Dis 3: e431. doi: 10.1371/journal.pntd.0000431
[24]
Scott D, Senker K, England EC (1982) Epidemiology of human Schistosoma haematobium infection around Volta Lake, Ghana, 1973–75. Bull World Health Organ 60: 89–100.
[25]
Paperna I (1970) Study of an outbreak of schistosomiasis in the newly formed Volta lake in Ghana. Z Tropenmed Parasitol 21: 411–425.
[26]
Chu KY, Klumpp RK, Kofi DY (1981) Results of three years of cercarial transmission control in the Volta Lake. Bull World Health Organ 59: 549–554.
[27]
Wen ST, Chu KY (1984) Preliminary schistosomiasis survey in the lower Volta River below Akosombo Dam, Ghana. Ann Trop Med Parasitol 78: 129–133.
[28]
Klumpp RK, Webbe G (1987) Focal, seasonal and behavioural patterns of infection and transmission of Schistosoma haematobium in a farming village at the Volta Lake, Ghana. J Trop Med Hyg 90: 265–281.
[29]
Hunter JM (2003) Inherited burden of disease: agricultural dams and the persistence of bloody urine (Schistosomiasis hematobium) in the Upper East Region of Ghana, 1959–1997. Soc Sci Med 56: 219–234. doi: 10.1016/S0277-9536(02)00021-7
[30]
Lyons GR (1974) Schistosomiasis in north-western Ghana. Bull World Health Organ 51: 621–632.
[31]
Nsowah-Nuamah NN, Mensah G, Aryeetey ME, Wagatsuma Y, Bentil G (2001) Urinary schistosomiasis in southern Ghana: a logistic regression approach to data from a community-based integrated control program. Am J Trop Med Hyg 65: 484–490.
[32]
Aryeetey ME, Wagatsuma Y, Yeboah G, Asante M, Mensah G, et al. (2000) Urinary schistosomiasis in southern Ghana: 1. Prevalence and morbidity assessment in three (defined) rural areas drained by the Densu river. Parasitol Int 49: 155–163. doi: 10.1016/S1383-5769(00)00044-1
[33]
Wagatsuma Y, Aryeetey ME, Nkrumah FK, Sack DA, Kojima S (2003) Highly symptom-aware children were heavily infected with urinary schistosomiasis in southern Ghana. Cent Afr J Med 49: 16–19.
[34]
Bosompem KM, Bentum IA, Otchere J, Anyan WK, Brown CA, et al. (2004) Infant schistosomiasis in Ghana: a survey in an irrigation community. Trop Med Int Health 9: 917–922. doi: 10.1111/j.1365-3156.2004.01282.x
[35]
Garba A, Toure S, Dembele R, Bosque-Oliva E, Fenwick A (2006) Implementation of national schistosomiasis control programmes in West Africa. Trends Parasitol 22: 322–326. doi: 10.1016/j.pt.2006.04.007
[36]
Katz N, Chaves A, Pellegrino J (1972) A simple device for quantitative stool thick-smear technique in schistosomiasis mansoni. Rev Inst Med Trop Sao Paulo 397–400.
[37]
Hay SI, Tatem AJ, Graham AJ, Goetz SJ, Rogers DJ (2006) Global environmental data for mapping infectious disease distribution. Adv Parasitol 62: 37–77. doi: 10.1016/S0065-308X(05)62002-7
[38]
Hosmer DW, Lemeshow S (2000) Applied Logistic Regression. New York: John Wiley and Sons, Inc.
[39]
WHO (2002) Prevention and Control of Schistosomiasis and Soil-Transmitted Helminthiasis. Geneva: World Health Organization. 57 p.
[40]
Alexander N, Moyeed R, Stander J (2000) Spatial modelling of individual-level parasite counts using the negative binomial distribution. Biostatistics 1: 453–463. doi: 10.1093/biostatistics/1.4.453
[41]
Anderson RM, May RM (1985) Helminth infections of humans: mathematical models, population dynamics, and control. Adv Parasitol 24: 1–101. doi: 10.1016/s0065-308x(08)60561-8
[42]
Utzinger J, Booth M, N'Goran EK, Muller I, Tanner M, et al. (2001) Relative contribution of day-to-day and intra-specimen variation in faecal egg counts of Schistosoma mansoni before and after treatment with praziquantel. Parasitology 122: 537–544. doi: 10.1017/S0031182001007752
[43]
Filipe JA, Boussinesq M, Renz A, Collins RC, Vivas-Martinez S, et al. (2005) Human infection patterns and heterogeneous exposure in river blindness. Proc Natl Acad Sci U S A 102: 15265–15270. doi: 10.1073/pnas.0502659102
[44]
Pion SD, Filipe JA, Kamgno J, Gardon J, Basanez MG, et al. (2006) Microfilarial distribution of Loa loa in the human host: population dynamics and epidemiological implications. Parasitology 133: 101–109. doi: 10.1017/S0031182006000035
[45]
Lambert D (1992) Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics 34: 1–14. doi: 10.2307/1269547
[46]
Diggle PJT, A , Moyeed RAB, N , Tawn JAL, D , Arnold R, Spiegelhalter D (2004) Model-based Geostatistics GeoBUGS User Manual version 1.2. Applied Statistics. Cambridge: Medical Research Council Biostatistics Unit. pp. 299–350.
[47]
Thomas A, Best N, Lunn D, Arnold R, Spiegelhalter D (2004) GeoBUGS User Manual version 1.2. Cambridge: Medical Research Council Biostatistics Unit.
[48]
Brooker S, Hay SI, Bundy DA (2002) Tools from ecology: useful for evaluating infection risk models? Trends Parasitol 18: 70–74. doi: 10.1016/S1471-4922(01)02223-1
[49]
Raso G, Vounatsou P, McManus DP, Utzinger J (2007) Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist. Geospat Health 2: 85–96.
[50]
Hall A, Holland C (2000) Geographical variation in Ascaris lumbricoides fecundity and its implications for helminth control. Parasitol Today 16: 540–544. doi: 10.1016/S0169-4758(00)01779-8
[51]
Tarafder MR, Carabin H, Joseph L, Balolong EJ, Olveda R, et al. (2010) Estimating the sensitivity and specificity of Kato-Katz stool examination technique for detection of hookworms, Ascaris lumbricoides and Trichuris trichiura infections in humans in the absence of a ‘gold standard’. Int J Parasitol 40: 399–404. doi: 10.1016/j.ijpara.2009.09.003
[52]
Drake LJ, Bundy DA (2001) Multiple helminth infections in children: impact and control. Parasitology 122: SupplS73–81. doi: 10.1017/S0031182000017662
[53]
Hotez PJ, Bundy DAP, Beegle K, Brooker S, Drake L, et al. (2006) Helminth Infections: Soil–Transmitted Helminth Infections and Schistosomiasis. Disease Control Priorities in Developing Countries 2nd ed. New York: Oxford University Press. pp. 467–482.
[54]
Ezeamama AE, Friedman JF, Olveda RM, Acosta LP, Kurtis JD, et al. (2005) Functional significance of low-intensity polyparasite helminth infections in anemia. J Infect Dis 192: 2160–2170. doi: 10.1086/498219
[55]
Hall A, Fentiman A (1999) Blood in the urine of adolescent girls in an area of Ghana with a low prevalence of infection with Schistosoma haematobium. Trans R Soc Trop Med Hyg 93: 411–412. doi: 10.1016/S0035-9203(99)90138-4
[56]
Engels D, Nahimana S, Gryseels B (1996) Comparison of the direct faecal smear and two thick smear techniques for the diagnosis of intestinal parasitic infections. Trans R Soc Trop Med Hyg 90: 523–525. doi: 10.1016/S0035-9203(96)90304-1
[57]
Booth M, Vounatsou P, N'Goran EK, Tanner M, Utzinger J (2003) The influence of sampling effort and the performance of the Kato-Katz technique in diagnosing Schistosoma mansoni and hookworm co-infections in rural Cote d'Ivoire. Parasitology 127: 525–531. doi: 10.1017/S0031182003004128
[58]
Wang XH, Zhou XN, Vounatsou P, Chen Z, Utzinger J, et al. (2008) Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic ‘gold’ standard. PLoS Negl Trop Dis 2: e250. doi: 10.1371/journal.pntd.0000250
[59]
Pullan RL, Bethony JM, Geiger SM, Correa-Oliveira R, Brooker S, et al. (2009) Human helminth co-infection: No evidence of common genetic control of hookworm and Schistosoma mansoni infection intensity in a Brazilian community. Int J Parasitol 40: 299–306. doi: 10.1016/j.ijpara.2009.08.002
[60]
Hutcheon JA, Chiolero A, Hanley JA (2010) Random measurement error and regression dilution bias. Br Med J 340: c2289. doi: 10.1136/bmj.c2289
[61]
Majumdar A, Gelfand AE (2007) Multivariate spatial modeling for geostatistical data using convolved covariance functions. Math Geol 39: 225–245. doi: 10.1007/s11004-006-9072-6
[62]
Ezeamama AE, McGarvey ST, Acosta LP, Zierler S, Manalo DL, et al. (2008) The synergistic effect of concomitant schistosomiasis, hookworm, and trichuris infections on children's anemia burden. PLoS Negl Trop Dis 2: e245. doi: 10.1371/journal.pntd.0000245
