Stochastic lattice-based modelling of malaria dynamics

Malaria Journal

Volumn 17, Issue 1, 2018, Pages

  Le, Phong V V ^a,b   Kumar, Praveen ^a,c   Ruiz, Marilyn O ^c  

^a United States of America   (United States)

^b VIETNAM NATIONAL UNIVERSITY   (Viet Nam)

^c UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

Climate change; Ecohydrology; Malaria; Metapopulation; Stochastic

Indexed keywords

ARTICLE; CONTROLLED STUDY; ENVIRONMENTAL CHANGE; EPIDEMIC; HOST PARASITE INTERACTION; HUMAN; INFECTION SENSITIVITY; KENYA; LIFE CYCLE; MALARIA; MOSQUITO; MOSQUITO VECTOR; NONHUMAN; PREDICTION; PREVALENCE; RURAL AREA; SIMULATION; STOCHASTIC LATTICE BASED MODEL; STOCHASTIC MODEL; ANIMAL; ANOPHELES; MARKOV CHAIN; PARASITOLOGY; PHYSIOLOGY; PLASMODIUM; RURAL POPULATION; THEORETICAL MODEL; TRANSMISSION;

ANIMALS; ANOPHELES; HUMANS; KENYA; MALARIA; MODELS, THEORETICAL; MOSQUITO VECTORS; PLASMODIUM; RURAL POPULATION; STOCHASTIC PROCESSES;

EID: 85049498996     PISSN: None     EISSN: 14752875     Source Type: Journal    
DOI: 10.1186/s12936-018-2397-z     Document Type: Article

References (46)

1. Miller LH, Baruch DI, Marsh K, Doumbo OK. The pathogenic basis of malaria. Nature. 2002;415:673-9.
2. Smith DL, McKenzie EF. Statics and dynamics of malaria infection in Anopheles mosquitoes. Malar J. 2004;3:1-14.
3. Anderson RM. The population dynamics of infectious diseases: theory and applications. Population and community biology series. London: Chapman & Hall Ltd.; 1982.
4. Anderson RM, May RM. Infectious diseases of humans: dynamics and control. Dynamics and control. Oxford: Oxford University Press; 1992.
5. Paaijmans KP, Thomas MB. Health: wealth versus warming. Nat Clim Change. 2011;1:349-50.
6. Caminade C, Kovats S, Rocklov J, Tompkins AM, Morse AP, Colón-González FJ, et al. Impact of climate change on global malaria distribution. Proc Natl Acad Sci USA. 2014;111:3286-91.
7. Ross R. The prevention of malaria. 2nd ed. Dutton; 1910.
8. MacDonald G. The Epidemiology and Control of Malaria. Oxford Medical Publications. Oxford, UK: Oxford University Press; 1957.
9. Ngwa GA, Shu WS. A mathematical model for endemic malaria with variable human and mosquito populations. Math Comput Model. 2000;32:747-63.
10. Chitnis N, Cushing J, Hyman J. Bifurcation analysis of a mathematical model for malaria transmission. SIAM J Appl Math. 2006;67:24-45.
11. Yang HM. Malaria transmission model for different levels of acquired immunity and temperature-dependent parameters (vector). Rev Saude Publica. 2000;34:223-31.
12. Filipe JAN, Riley EM, Drakeley CJ, Sutherland CJ, Ghani AC. Determination of the processes driving the acquisition of immunity to malaria using a mathematical transmission model. PLoS Comput Biol. 2007;3:e255.
13. Parham PE, Michael E. Modeling the effects of weather and climate change on malaria transmission. Environ Health Perspect. 2010;118:620-6.
14. Ariey F, Duchemin JB, Robert V. Metapopulation concepts applied to falciparum malaria and their impacts on the emergence and spread of chloroquine resistance. Infect Genet Evol. 2003;2:185-92.
15. Bomblies A, Duchemin JB, Eltahir EAB. Hydrology of malaria: model development and application to a Sahelian village. Water Resour Res. 2008;44:W12445.
16. Gu W, Novak RJ. Agent-based modelling of mosquito foraging behaviour for malaria control. Trans R Soc Trop Med Hyg. 2009;103:1105-12.
17. Arifin SN, Zhou Y, Davis GJ, Gentile JE, Madey GR, Collins FH. An agent-based model of the population dynamics of Anopheles gambiae. Malar J. 2014;13:1-20.
18. Pizzitutti F, Pan W, Barbieri A, Miranda JJ, Feingold B, Guedes GR, et al. A validated agent-based model to study the spatial and temporal heterogeneities of malaria incidence in the rainforest environment. Malar J. 2015;14:1-19.
19. Mandal S, Sarkar R, Sinha S. Mathematical models of malaria - a review. Malar J. 2011;10:202.
20. Reiner RC, Perkins TA, Barker CM, et al. A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970-2010. J R Soc Interface. 2013;10:20120921.
21. Smith DL, Perkins TA, Reiner RC, Barker CM, Niu T, Chaves LF, et al. Recasting the theory of mosquito-borne pathogen transmission dynamics and control. Trans R Soc Trop Med Hyg. 2014;108:185-97.
22. Keeling MJ, Rohani P. Modeling infectious diseases in humans and animals. Princeton: Princeton University Press; 2008.
23. Azaele S, Maritan A, Bertuzzo E, Rodriguez-Iturbe I, Rinaldo A. Stochastic dynamics of cholera epidemics. Phys Rev E. 2010;81:051901.
24. Herwaarden OA, Grasman J. Stochastic epidemics: major outbreaks and the duration of the endemic period. J Math Biol. 1995;33:581-601.
25. van Herwaarden AO. Stochastic epidemics: the probability of extinction of an infectious disease at the end of a major outbreak. J Math Biol. 1997;35:793-813.
26. Britton T. Stochastic epidemic models: a survey. Math Biosci. 2010;225:24-35.
27. Krstic M. The effect of stochastic perturbation on a nonlinear delay malaria epidemic model. Math Comput Simul. 2011;82:558-69.
28. Lutambi AM, Penny MA, Smith T, Chitnis N. Mathematical modelling of mosquito dispersal in a heterogeneous environment. Math Biosci. 2013;241:198-216.
29. Depinay JM, Mbogo C, Killeen G, Knols B, Beier J, Carlson J, et al. A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission. Malar J. 2004;3:29.
30. Allen E. Modeling with Itô Stochastic differential equations. Mathematical modelling: theory and applications. Heidelberg, Germany: Springer Berlin Heidelberg; 2007.
31. Allen LJS. An introduction to stochastic processes with applications to biology. 2nd ed. Florida: CRC Press; 2010.
32. Doolan DL, Dobaño C, Baird JK. Acquired immunity to malaria. Clin Microbiol Rev. 2009;22:13-36.
33. Detinova TS. Age-grouping methods in Diptera of medical importance with special reference to some vectors of malaria. WHO Monograph series. 1962;47:13-191.
34. Briere JF, Pracros P, Le Roux AY, Pierre JS. A novel rate model of temperature-dependent development for arthropods. Environ Entomol. 1999;28:22-9.
35. Paaijmans KP, Read AF, Thomas MB. Understanding the link between malaria risk and climate. Proc Natl Acad Sci USA. 2009;106:13844-9.
36. Le PVV, Kumar P. Interaction between ecohydrologic dynamics and microtopographic variability under climate change. Water Resour Res. 2017;53:8383-403.
37. Drewry DT, Kumar P, Long S, Bernacchi C, Liang XZ, Sivapalan M. Ecohydrological responses of dense canopies to environmental variability: 1. Interplay between vertical structure and photosynthetic pathway. J Geophys Res. 2010;115:G04022.
38. Le PVV, Kumar P, Drewry DT, Quijano JC. A graphical user interface for numerical modeling of acclimation responses of vegetation to climate change. Comput Geosci. 2012;49:91-101.
39. Le PVV, Kumar P, Drewry DT. Implications for the hydrologic cycle under climate change due to the expansion of bioenergy crops in the Midwestern United States. Proc Natl Acad Sci USA. 2011;108:15085-90.
40. Le PVV, Kumar P, Valocchi AJ, Dang HV. GPU-based high-performance computing for integrated surface-sub-surface flow modeling. Environ Modell Softw. 2015;73:1-13.
41. Le PVV, Kumar P. Power law scaling of topographic depressions and their hydrologic connectivity. Geophys Res Lett. 2014;41:1553-9.
42. Nyakeriga AM, Troye-Blomberg M, Chemtai AK, Marsh K, Williams TN. Malaria and nutritional status in children living on the coast of Kenya. Am J Clin Nutr. 2004;80:1604-10.
43. Snow RW, Kibuchi E, Karuri SW, Sang G, Gitonga CW, Mwandawiro C, et al. Changing malaria prevalence on the Kenyan Coast since 1974: climate, drugs and vector control. PLoS ONE. 2015;10:1-14.
44. Mogeni P, Williams TN, Fegan G, Nyundo C, Bauni E, Mwai K, et al. Age, spatial, and temporal variations in hospital admissions with malaria in Kilifi County, Kenya: a 25-year longitudinal observational study. PLoS Med. 2016;13:1-17.
45. Le PVV, Kumar P, Ruiz MO, Mbogo C, Muturi JE. Predicting the direct and indirect impacts of climate change on malaria in coastal Kenya. PLOS (under review). 2018.
46. Tatem AJ, Noor AM, von Hagen C, Di Gregorio A, Hay SI. High resolution population maps for low income nations: combining land cover and census in East Africa. PLoS ONE. 2007;2:1-8.