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

References

• WHO. World malaria report. 2012; Geneva: World Health Organization.
   Google Scholar
• Hay SI, Snow RW. The malaria atlas project: developing global maps of malaria risk. PLoS Med. 2006; 3: e473. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Hay SI, Guerra CA, Gething PW, Patil AP, Tatem AJ, Noor AM, etal. A world malaria map: Plasmodium falciparum endemicity in 2007. PLoS Med. 2009; 6: e1000048. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Parham PE, Michael E. Modeling the effects of weather and climate change on malaria transmission. Environ Health Perspect. 2010; 118: 620–6. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Fontenille D, Lochouarn L, Diatta M, Sokhna C, Dia I, Diagne N, etal. 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. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Mboera LEG, Senkoro KP, Mayala BK, Rumisha SF, Rwegoshora RT, Mlozi MRS, etal. Spatio-temporal variation in malaria transmission intensity in five agro-ecosystems in Mvomero district, Tanzania. Geospat Health. 2010; 4: 167–78. [PubMed Abstract].
   Google Scholar
• Nedelman J. A negative binomial model for sampling mosquitoes in a malaria survey. Biometrics. 1983; 39: 1009–20. [PubMed Abstract].
   Google Scholar
• Alexander N, Moyeed R, Stander J. Spatial modelling of individual-level parasite counts using the negative binomial distribution. Biostatistics. 2000; 1: 453–63. [PubMed Abstract].
   Google Scholar
• Michael E. Quantifying mosquito biting patterns on humans by DNA fingerprinting of bloodmeals. Am J Trop Med Hyg. 2001; 65: 722. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Smith T, Charlwood JD, Kihonda J, Mwankusye S, Billingsley P, Meuwissen J, etal. Absence of seasonal variation in malaria parasitaemia in an area of intense seasonal transmission. Acta Tropica. 1993; 54: 55–72. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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.
   PubMedGoogle Scholar
• Woolhouse MEJ, Dye C, Etard J-F, Smith T, Charlwood JD, Garnett GP, etal. 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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/contentdelivery/servlet/ERICServlet?accno=ED401316 [cited 23 August 2013]..
   Google Scholar
• Smith TA, Leuenberger R, Lengeler C. Child mortality and malaria transmission intensity in Africa. Trends Parasitol. 2001; 17: 145–9. [PubMed Abstract].
   Google Scholar
• Thomson MC, Connor SJ. The development of malaria early warning systems for Africa. Trends Parasitol. 2001; 17: 438–45. [PubMed Abstract].
   Google Scholar
• Sankoh OA, Binka F. Takken W, Martens P, Bogers RJ. INDEPTH Network: a viable platform for the assessment of malaria risk in developing countries. Environmental change and malaria risk-global and local implications. 2005; Berlin: Springer Verlag.
   Google Scholar
• Gatton M. Environmental factors and malaria transmission risk. Lancet Infect Dis. 2010; 10: 15–6.
   Google Scholar
• Killeen GF, Tami A, Kihonda J, Okumu FO, Kotas ME, Grundmann H, etal. 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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.
   Web of Science ®Google Scholar
• Chase JM, Shulman RS. Wetland isolation facilitates larval mosquito density through the reduction of predators. Ecol Entomol. 2009; 34: 741–7.
   Web of Science ®Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Kasasa S, Asoala V, Gosoniu L, Anto F, Adjuik M, Tindana C, etal. Spatio-temporal malaria transmission patterns in Navrongo demographic surveillance site, northern Ghana. Malar J. 2013; 12: 63. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Greene WH. Accounting for excess zeros and sample selection in Poisson and negative binomial regression models. 1994; Leonard N. Stern School of Business: Technical report. New York: New York University. 34.
   Google Scholar
• Cheung YB. Zero-inflated models for regression analysis of count data: a study of growth and development. Stat Med. 2002; 21: 1461–9. [PubMed Abstract].
   Google Scholar
• 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.
   Web of Science ®Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Agarwal DK, Gelfand AE, Citron-Pousty S. Zero-inflated models with application to spatial count data. Environ Ecol Stat. 2002; 9: 341–55.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• Sogoba N, Vounatsou P, Doumbia S, Bagayoko M, Touré MB, Sissoko IM, etal. 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. [PubMed Abstract].
   Google Scholar
• Cressie NAC. Statistics for spatial data. 1993; New York: Wiley-Interscience.
   Google Scholar
• Diggle PJ, Tawn JA, Moyeed RA. Model-based geostatistics. J Roy Stat Soc C Appl Stat. 1998; 47: 299–350.
   Web of Science ®Google Scholar
• Gelfand AE, Smith AFM. Sampling-based approaches to calculating marginal densities. J Am Stat Assoc. 1990; 85: 398–409.
   Web of Science ®Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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.
   Web of Science ®Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Rumisha SF. Modelling the seasonal and spatial variation of malaria transmission in relation to mortality in Africa. 2013; PhD thesis, University of Basel, Basel, Switzerland.
   Google Scholar
• 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. 2002; Ottawa: IDRC/CRDI.
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Rau R. Seasonality in human mortality – a demographic approach. 1st ed. 2006; Springer. Available from: http://www.springer.com/economics/population/book/978-3-540-44900-3 [cited 23 Aug 2013]..
   Google Scholar
• Lambert D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics. 1992; 34: 1–14.
   Web of Science ®Google Scholar
• 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]..
   Google Scholar
• Xia G, Gelfand AE. Stationary process approximation for the analysis of large spatial datasets. Technical Report. 2005; Durham, NC: ISDS, Duke University.
   Google Scholar
• Johnson ME, Moore LM, Ylvisaker D. Minimax and maximin distance designs. J Stat Plann Infer. 1990; 26: 131–48.
   Web of Science ®Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Gosoniu L, Vounatsou P, Sogoba N, Smith T. Bayesian modelling of geostatistical malaria risk data. Geospat Health. 2006; 1: 127–39. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Amek N, Bayoh N, Hamel M, Lindblade KA, Gimnig JE, Odhiambo F, etal. Spatial and temporal dynamics of malaria transmission in rural Western Kenya. Parasites & Vectors. 2012; 5: 86. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Hastings WK. Monte Carlo sampling methods using Markov chains and their applications. Biometrika. 1970; 57: 97–109.
   Web of Science ®Google Scholar
• Metropolis N. The beginning of the Monte Carlo method. Los Alamos Science. 1987; 15: 125.
   Google Scholar
• Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Statist Sci. 1992; 7: 457–72.
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Gosoniu L. Development of Bayesian geostatistical models with applications in malaria epidemiology [doctoral]. 2008; University of Basel. Available from: http://ihi.eprints.org/1131/ [cited 23 August 2013]..
   Google Scholar
• Reid H, Vallely A, Taleo G, Tatem AJ, Kelly G, Riley I, etal. Baseline spatial distribution of malaria prior to an elimination programme in Vanuatu. Malar J. 2010; 9: 150. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Amek N, Bayoh N, Hamel M, Lindblade KA, Gimnig J, Laserson KF, etal. Spatio-temporal modeling of sparse geostatistical malaria sporozoite rate data using a zero inflated binomial model. Spat Spatiotemporal Epidemiol. 2011; 2: 283–90. [PubMed Abstract].
   Google Scholar
• Gething PW, Patil AP, Smith DL, Guerra CA, Elyazar IRF, Johnston GL, etal. A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J. 2011; 10: 378. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Giardina F, Gosoniu L, Konate L, Diouf MB, Perry R, Gaye O, etal. Estimating the Burden of Malaria in Senegal: Bayesian Zero-Inflated Binomial Geostatistical Modeling of the MIS 2008 Data. PLoS ONE. 2012; 7: e32625. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• 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.
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Warrell DA, Gilles HM. Essential malariology. 2003; London, UK: Arnold. 4th edition.
   Google Scholar
• Guelbeogo WM, Sagnon N, Grushko O, Yameogo MA, Boccolini D, Besansky NJ, etal. Seasonal distribution of Anopheles funestus chromosomal forms from Burkina Faso. Malar J. 2009; 8: 239. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Adja AM, N'goran EK, Koudou BG, Dia I, Kengne P, Fontenille D, etal. Contribution of Anopheles funestus, An. gambiae and An. nili (Diptera: Culicidae) to the perennial malaria transmission in the southern and western forest areas of Côte d'Ivoire. Ann Trop Med Parasitol. 2011; 105: 13–24. [PubMed Abstract].
   Google Scholar
• Charlwood JD, Qassim M, Elnsur EI, Donnelly M, Petrarca V, Billingsley PF, etal. The impact of indoor residual spraying with malathion on malaria in refugee camps in eastern Sudan. Acta Trop. 2001; 80: 1–8. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• 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. [PubMed Abstract].
   Google Scholar
• Drakeley CJ, Carneiro I, Reyburn H, Malima R, Lusingu JPA, Cox J, etal. Altitude-dependent and -independent variations in Plasmodium falciparum prevalence in northeastern Tanzania. J Infect Dis. 2005; 191: 1589–98. [PubMed Abstract].
   Google Scholar
• Stewart L, Gosling R, Griffin J, Gesase S, Campo J, Hashim R, etal. Rapid assessment of malaria transmission using age-specific sero-conversion rates. PLoS ONE. 2009; 4: e6083. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar
• Bousema T, Okell L, Shekalaghe S, Griffin JT, Omar S, Sawa P, etal. 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. [PubMed Abstract] [PubMed CentralFull Text].
   Google Scholar