Modelling heterogeneity in malaria transmission using large sparse spatio-temporal entomological data

Global Health Action

Volumn 7, Issue 1, 2014, Pages 1-13

  Rumisha, Susan Fred ^a,b,c   Smith, Thomas ^a,b   Abdulla, Salim ^d   Masanja, Honorath ^d   Vounatsou, Penelope ^a,b  

^a SWISS TROPICAL AND PUBLIC HEALTH INSTITUTE   (Switzerland)

^b UNIVERSITY OF BASEL   (Switzerland)

^c NATIONAL INSTITUTE FOR MEDICAL RESEARCH   (Tanzania)

^d IFAKARA HEALTH INSTITUTE   (Tanzania)

Author keywords

Approximate spatial process; INDEPTH MTIMBA; Malaria transmission; MCMC; Seasonality

Indexed keywords

RAIN;

ANIMAL; ANOPHELES; BAYES THEOREM; BIOLOGICAL MODEL; HUMAN; MALARIA; PARASITOLOGY; POPULATION DENSITY; SEASON; SPATIOTEMPORAL ANALYSIS; TANZANIA; TEMPERATURE; TRANSMISSION;

ANIMALS; ANOPHELES; BAYES THEOREM; HUMANS; MALARIA; MODELS, BIOLOGICAL; POPULATION DENSITY; RAIN; SEASONS; SPATIO-TEMPORAL ANALYSIS; TANZANIA; TEMPERATURE;

EID: 84925223327     PISSN: None     EISSN: 16549880     Source Type: Journal    
DOI: 10.3402/gha.v7.22682     Document Type: Article

References (77)

1. WHO (2012). World malaria report. Geneva: World Health Organization.
2. Hay SI, Snow RW. The malaria atlas project: developing global maps of malaria risk. PLoS Med 2006; 3: e473.
3. Hay SI, Guerra CA, Gething PW, Patil AP, Tatem AJ, Noor AM, et al. A world malaria map: Plasmodium falciparum endemicity in 2007. PLoS Med 2009; 6: e1000048.
4. Parham PE, Michael E. Modeling the effects of weather and climate change on malaria transmission. Environ Health Perspect 2010; 118: 620-6.
5. Fontenille D, Lochouarn L, Diatta M, Sokhna C, Dia I, Diagne N, et al. Four years' entomological study of the transmission of seasonal malaria in Senegal and the bionomics of Anopheles gambiae and A. arabiensis. Trans R Soc Trop Med Hyg 1997; 91: 647-52.
6. Beier JC, Killeen GF, Githure JI. Short report: entomologic inoculation rates and Plasmodium falciparum malaria prevalence in Africa. Am J Trop Med Hyg 1999; 61: 109-13.
7. Hay SI, Rogers DJ, Toomer JF, Snow RW. Annual Plasmodium falciparum entomological inoculation rates (EIR) across Africa: literature survey, Internet access and review. Trans R Soc Trop Med Hyg 2000; 94: 113-27.
8. Mboera LEG, Senkoro KP, Mayala BK, Rumisha SF, Rwegoshora RT, Mlozi MRS, et al. Spatio-temporal variation in malaria transmission intensity in five agro-ecosystems in Mvomero district, Tanzania. Geospat Health 2010; 4: 167-78.
9. Nedelman J. A negative binomial model for sampling mosquitoes in a malaria survey. Biometrics 1983; 39: 1009-20.
10. Alexander N, Moyeed R, Stander J. Spatial modelling of individual-level parasite counts using the negative binomial distribution. Biostatistics 2000; 1: 453-63.
11. Michael E. Quantifying mosquito biting patterns on humans by DNA fingerprinting of bloodmeals. Am J Trop Med Hyg 2001; 65: 722.
12. Shaukat AM, Breman JG, McKenzie FE. Using the entomological inoculation rate to assess the impact of vector control on malaria parasite transmission and elimination. Malar J 2010; 9: 122.
13. Smith T, Charlwood JD, Kihonda J, Mwankusye S, Billingsley P, Meuwissen J, et al. Absence of seasonal variation in malaria parasitaemia in an area of intense seasonal transmission. Acta Tropica 1993; 54: 55-72.
14. Killeen GF, McKenzie FE, Foy BD, Schieffelin C, Billingsley PF, Beier JC. A simplified model for predicting malaria entomologic inoculation rates based on entomologic and parasitologic parameters relevant to control. Am J Trop Med Hyg 2000; 62: 535-44.
15. Lee HI, Lee JS, Shin EH, Lee WJ, Kim YY, Lee KR. Malaria transmission potential by Anopheles sinensis in the Republic of Korea. Korean J Parasitol 2001; 39: 185-92.
16. Kelly-Hope LA, McKenzie FE. The multiplicity of malaria transmission: a review of entomological inoculation rate measurements and methods across sub-Saharan Africa. Malar J 2009; 8: 19.
17. Snow RW, Craig MH, Deichmann U, le Sueur D. A preliminary continental risk map for malaria mortality among African children. Parasitol Today (Regul Ed) 1999; 15: 99-104.
18. Woolhouse MEJ, Dye C, Etard J-F, Smith T, Charlwood JD, Garnett GP, et al. Heterogeneities in the transmission of infectious agents: implications for the design of control programs. Proc Natl Acad Sci U S A 1997; 94: 338-42.
19. Brogan R, Zhao C. Designing a longitudinal study [microform]: issues, problems & concerns. [S.l.]: distributed by ERIC Clearinghouse; 1992. Available from: http://www.eric.ed.gov/content delivery/servlet/ERICServlet?accno=ED401316 [cited 23 August 2013].
20. Smith TA, Leuenberger R, Lengeler C. Child mortality and malaria transmission intensity in Africa. Trends Parasitol 2001; 17: 145-9.
21. Thomson MC, Connor SJ. The development of malaria early warning systems for Africa. Trends Parasitol 2001; 17: 438-45.
22. Sankoh OA, Binka F. INDEPTH Network: a viable platform for the assessment of malaria risk in developing countries. In: Takken W, Martens P, Bogers RJ, eds. Environmental change and malaria risk-global and local implications. Berlin: Springer Verlag; 2005.
23. Gatton M. Environmental factors and malaria transmission risk. Lancet Infect Dis 2010; 10: 15-6.
24. Killeen GF, Tami A, Kihonda J, Okumu FO, Kotas ME, Grundmann H, et al. Cost-sharing strategies combining targeted public subsidies with private-sector delivery achieve high bednet coverage and reduced malaria transmission in Kilombero Valley, southern Tanzania. BMC Infect Dis 2007; 7: 121.
25. Leisnham PT, Slaney DP, Lester PJ, Weinstein P, Heath ACG. Mosquito density, macroinvertebrate diversity, and water chemistry in water-filled containers: relationships to land use. New Zeal J Zool 2007; 34: 203-18.
26. Chase JM, Shulman RS. Wetland isolation facilitates larval mosquito density through the reduction of predators. Ecol Entomol 2009; 34: 741-7.
27. Kweka EJ, Mwang'onde BJ, Mahande AM. Optimization of odour-baited resting boxes for sampling malaria vector, Anopheles arabiensis Patton, in arid and highland areas of Africa. Parasit Vectors 2010; 3: 75.
28. Kasasa S, Asoala V, Gosoniu L, Anto F, Adjuik M, Tindana C, et al. Spatio-temporal malaria transmission patterns in Navrongo demographic surveillance site, northern Ghana. Malar J 2013; 12: 63.
29. Greene WH. Accounting for excess zeros and sample selection in Poisson and negative binomial regression models. Technical report. New York: New York University, Leonard N. Stern School of Business; 1994, 34 p.
30. Cheung YB. Zero-inflated models for regression analysis of count data: a study of growth and development. Stat Med 2002; 21: 1461-9.
31. Yau KKW, Wang K, Lee AH. Zero-inflated negative binomial mixed regression modeling of over-dispersed count data with extra zeros. Biometrical J 2003; 45: 437-52.
32. Ryan PA, Lyons SA, Alsemgeest D, Thomas P, Kay BH. Spatial statistical analysis of adult mosquito (Diptera: Culicidae) counts: an example using light trap data, in Redland Shire, Southeastern Queensland, Australia. J Med Entomol 2004; 41: 1143-56.
33. Ridout M, Hinde J, DeméAtrio CGB. A score test for testing a zero-inflated Poisson regression model against zero-inflated negative binomial alternatives. Biometrics 2001; 57: 219-23.
34. Agarwal DK, Gelfand AE, Citron-Pousty S. Zero-inflated models with application to spatial count data. Environ Ecol Stat 2002; 9: 341-55.
35. Warton DI. Many zeros does not mean zero inflation: comparing the goodness-of-fit of parametric models to multivariate abundance data. Environmetrics 2005; 16: 275-89.
36. Sogoba N, Vounatsou P, Doumbia S, Bagayoko M, Touré MB, Sissoko IM, et al. 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.
37. Cressie NAC. Statistics for spatial data. New York: Wiley- Interscience; 1993.
38. Diggle PJ, Tawn JA, Moyeed RA. Model-based geostatistics. J Roy Stat Soc C Appl Stat 1998; 47: 299-350.
39. Gelfand AE, Smith AFM. Sampling-based approaches to calculating marginal densities. J Am Stat Assoc 1990; 85: 398-409.
40. Banerjee S, Gelfand AE, Finley AO, Sang H. Gaussian predictive process models for large spatial data sets. J R Stat Soc Series B Stat Methodol 2008; 70: 825-48.
41. Eidsvik J, Finley AO, Banerjee S, Rue H. Approximate Bayesian inference for large spatial datasets using predictive process models. Comput Stat Data Anal 2012; 56: 1362-80.
42. Finley AO, Sang H, Banerjee S, Gelfand AE. Improving the performance of predictive process modeling for large datasets. Comput Stat Data Anal 2009; 53: 2873-84.
43. Rumisha SF. Modelling the seasonal and spatial variation of malaria transmission in relation to mortality in Africa. PhD thesis, University of Basel, Basel, Switzerland, 2013.
44. Mwageni E, Momburi D, Juma Z, Irema M, Masanja H, TEHIP and AMMP Teams. INDEPTH monograph series: demographic surveillance systems for assessing populations and their health in developing countries. Ottawa: IDRC/CRDI; 2002.
45. Stolwijk AM, Straatman H, Zielhuis GA. Studying seasonality by using sine and cosine functions in regression analysis. J Epidemiol Community Health 1999; 53: 235-8.
46. Rau R. Seasonality in human mortality - a demographic approach. 1st ed. Springer; 2006. Available from: http://www. springer.com/economics/population/book/978-3-540-44900-3 [cited 23 Aug 2013].
47. Lambert D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics 1992; 34: 1-14.
48. Seeger M. Bayesian Gaussian Process Models: PAC-Bayesian generalisation error bounds and sparse approximations. 2003; Available from: http://www.era.lib.ed.ac.uk/handle/1842/321 [cited 23 Aug 2013].
49. Xia G, Gelfand AE. Stationary process approximation for the analysis of large spatial datasets. Technical Report. Durham, NC: ISDS, Duke University; 2005.
50. Johnson ME, Moore LM, Ylvisaker D. Minimax and maximin distance designs. J Stat Plann Infer 1990; 26: 131-48.
51. Hay JL, Pettitt AN. Bayesian analysis of a time series of counts with covariates: an application to the control of an infectious disease. Biostatistics 2001; 2: 433-44.
52. Gosoniu L, Vounatsou P, Sogoba N, Smith T. Bayesian modelling of geostatistical malaria risk data. Geospat Health 2006; 1: 127-39.
53. Lines JD, Wilkes TJ, Lyimo EO. Human malaria infectiousness measured by age-specific sporozoite rates in Anopheles gambiae in Tanzania. Parasitology 1991; 102 Pt 2: 167-77.
54. Amek N, Bayoh N, Hamel M, Lindblade KA, Gimnig JE, Odhiambo F, et al. Spatial and temporal dynamics of malaria transmission in rural Western Kenya. Parasites & Vectors 2012; 5: 86.
55. Hastings WK. Monte Carlo sampling methods using Markov chains and their applications. Biometrika 1970; 57: 97-109.
56. Metropolis N. The beginning of the Monte Carlo method. Los Alamos Science 1987; 15: 125.
57. Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Statist Sci 1992; 7: 457-72.
58. Lloyd-Smith JO. Maximum likelihood estimation of the negative binomial dispersion parameter for highly overdispersed data, with applications to infectious diseases. PLoS One 2007; 2: e180.
59. Thomas CJ, Lindsay SW. Local-scale variation in malaria infection amongst rural Gambian children estimated by satellite remote sensing. Trans R Soc Trop Med Hyg 2000; 94: 159-63.
60. Gosoniu L. Development of Bayesian geostatistical models with applications in malaria epidemiology [doctoral]. University of Basel; 2008. Available from: http://ihi.eprints.org/1131/ [cited 23 August 2013].
61. Reid H, Vallely A, Taleo G, Tatem AJ, Kelly G, Riley I, et al. Baseline spatial distribution of malaria prior to an elimination programme in Vanuatu. Malar J 2010; 9: 150.
62. Amek N, Bayoh N, Hamel M, Lindblade KA, Gimnig J, Laserson KF, et al. Spatio-temporal modeling of sparse geostatistical malaria sporozoite rate data using a zero inflated binomial model. Spat Spatiotemporal Epidemiol 2011; 2: 283-90.
63. Gething PW, Patil AP, Smith DL, Guerra CA, Elyazar IRF, Johnston GL, et al. A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J 2011; 10: 378.
64. Giardina F, Gosoniu L, Konate L, Diouf MB, Perry R, Gaye O, et al. Estimating the Burden of Malaria in Senegal: Bayesian Zero-Inflated Binomial Geostatistical Modeling of the MIS 2008 Data. PLoS ONE 2012; 7: e32625.
65. Snow RW, Nahlen B, Palmer A, Donnelly CA, Gupta S, Marsh K. Risk of severe malaria among African infants: direct evidence of clinical protection during early infancy. J Infect Dis 1998; 177: 819-22.
66. Gillies MT, de Meillon B. The Anophelinae of Africa south of the Sahara (Ethiopian Zoogeographical Region). Publ S Afr Inst Med Res 1968; 54: 3-343 pp.
67. Charlwood JD, Vij R, Billingsley PF. Dry season refugia of malaria-transmitting mosquitoes in a dry savannah zone of east Africa. Am J Trop Med Hyg 2000; 62: 726-32.
68. Warrell DA, Gilles HM. Essential malariology. 4th edition. London, UK: Arnold; 2003.
69. Guelbeogo WM, Sagnon N, Grushko O, Yameogo MA, Boccolini D, Besansky NJ, et al. Seasonal distribution of Anopheles funestus chromosomal forms from Burkina Faso. Malar J 2009; 8: 239.
70. Adja AM, N'goran EK, Koudou BG, Dia I, Kengne P, Fontenille D, et al. Contribution of Anopheles funestus, An. gambiae and An. nili (Diptera: Culicidae) to the perennial malaria transmission in the southern and western forest areas of Cote d'Ivoire. Ann Trop Med Parasitol 2011; 105: 13-24.
71. Charlwood JD, Qassim M, Elnsur EI, Donnelly M, Petrarca V, Billingsley PF, et al. The impact of indoor residual spraying with malathion on malaria in refugee camps in eastern Sudan. Acta Trop 2001; 80: 1-8.
72. Kent RJ, Coetzee M, Mharakurwa S, Norris DE. Feeding and indoor resting behaviour of the mosquito Anopheles longipalpis in an area of hyperendemic malaria transmission in southern Zambia. Med Vet Entomol 2006; 20: 459-63.
73. Atieli H, Menya D, Githeko A, Scott T. House design modifications reduce indoor resting malaria vector densities in rice irrigation scheme area in western Kenya. Malar J 2009; 8: 108.
74. Thomson MC, Mason SJ, Phindela T, Connor SJ. Use of rainfall and sea surface temperature monitoring for malaria early warning in Botswana. Am J Trop Med Hyg 2005; 73: 214-21.
75. Drakeley CJ, Carneiro I, Reyburn H, Malima R, Lusingu JPA, Cox J, et al. Altitude-dependent and -independent variations in Plasmodium falciparum prevalence in northeastern Tanzania. J Infect Dis 2005; 191: 1589-98.
76. Stewart L, Gosling R, Griffin J, Gesase S, Campo J, Hashim R, et al. Rapid assessment of malaria transmission using agespecific sero-conversion rates. PLoS ONE 2009; 4: e6083.
77. Bousema T, Okell L, Shekalaghe S, Griffin JT, Omar S, Sawa P, et al. Revisiting the circulation time of Plasmodium falciparum gametocytes: molecular detection methods to estimate the duration of gametocyte carriage and the effect of gametocytocidal drugs. Malar J 2010; 9: 136.