malERA: An updated research agenda for combination interventions and modelling in malaria elimination and eradication
Richard Steketee and colleagues propose an updated research agenda for combination interventions and modelling in malaria elimination and eradication.
Vyšlo v časopise:
malERA: An updated research agenda for combination interventions and modelling in malaria elimination and eradication. PLoS Med 14(11): e32767. doi:10.1371/journal.pmed.1002453
Kategorie:
Collection Review
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pmed.1002453
Souhrn
Richard Steketee and colleagues propose an updated research agenda for combination interventions and modelling in malaria elimination and eradication.
Zdroje
1. malERA Consultative Group on Modeling. A research agenda for malaria eradication: modeling. PLoS Med. 2011;8(1):e1000403. doi: 10.1371/journal.pmed.1000403 21283605
2. The malERA Refresh Consultative Panel on Tools for Malaria Elimination. malERA: An updated research agenda for diagnostics, drugs, vaccines, and vector control in malaria elimination and eradication PLoS Med. 2017;14(11):e1002455. doi: 10.1371/journal.pmed.1002455
3. Rabinovich RN, Drakeley C, Djimde AA, Hall BF, Hay SI, Hemingway J, et al. malERA: An updated research agenda for malaria elimination and eradication. PLoS Med. 2017;14(11):e1002456. doi: 10.1371/journal.pmed.1002456
4. World Health Organization. World malaria report 2015 Geneva: WHO; 2015. Available from: http://www.who.int/malaria/publications/world-malaria-report-2015/report/en/.
5. World Health Organization. Global technical strategy for malaria 2016–2030 Geneva: WHO; 2015. Available from: http://apps.who.int/iris/bitstream/10665/176712/1/9789241564991_eng.pdf
6. Gething PW, Battle KE, Bhatt S, Smith DL, Eisele TP, Cibulskis RE, et al. Declining malaria in Africa: improving the measurement of progress. Malar J. 2014;13:39. doi: 10.1186/1475-2875-13-39 24479555
7. Battle KE, Guerra CA, Golding N, Duda KA, Cameron E, Howes RE, et al. Global database of matched Plasmodium falciparum and P. vivax incidence and prevalence records from 1985–2013. Sci Data. 2015;2:150012. doi: 10.1038/sdata.2015.12 26306203
8. Bejon P, White MT, Olotu A, Bojang K, Lusingu JP, Salim N, et al. Efficacy of RTS,S malaria vaccines: individual-participant pooled analysis of phase 2 data. Lancet Infect Dis. 2013;13(4):319–27. doi: 10.1016/S1473-3099(13)70005-7 23454164
9. Bhatt S, Weiss DJ, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526(7572):207–11. doi: 10.1038/nature15535 26375008
10. Blagborough AM, Churcher TS, Upton LM, Ghani AC, Gething PW, Sinden RE. Transmission-blocking interventions eliminate malaria from laboratory populations. Nat Commun. 2013;4:1812. doi: 10.1038/ncomms2840 23652000
11. Cameron E, Battle KE, Bhatt S, Weiss DJ, Bisanzio D, Mappin B, et al. Defining the relationship between infection prevalence and clinical incidence of Plasmodium falciparum malaria. Nat Commun. 2015;6:8170. doi: 10.1038/ncomms9170 26348689
12. Moyes CL, Temperley WH, Henry AJ, Burgert CR, Hay SI. Providing open access data online to advance malaria research and control. Malar J. 2013;12:161. doi: 10.1186/1475-2875-12-161 23680401
13. Wu L, van den Hoogen LL, Slater H, Walker PG, Ghani AC, Drakeley CJ, et al. Comparison of diagnostics for the detection of asymptomatic Plasmodium falciparum infections to inform control and elimination strategies. Nature. 2015;528(7580):S86–93. doi: 10.1038/nature16039 26633770
14. World Health Organization. From malaria control to malaria elimination: a manual for elimination scenario planning Geneva: WHO; 2014. Available from: http://apps.who.int/iris/bitstream/10665/112485/1/9789241507028_eng.pdf
15. Gerardin J, Ouedraogo AL, McCarthy KA, Eckhoff PA, Wenger EA. Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness. Malar J. 2015;14:231. doi: 10.1186/s12936-015-0751-y 26037226
16. Gerardin J, Bever CA, Hamainza B, Miller JM, Eckhoff PA, Wenger EA. Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission. PLoS Comput Biol. 2016;12(1):e1004707. doi: 10.1371/journal.pcbi.1004707 26764905
17. Marshall JM, White MT, Ghani AC, Schlein Y, Muller GC, Beier JC. Quantifying the mosquito's sweet tooth: modelling the effectiveness of attractive toxic sugar baits (ATSB) for malaria vector control. Malar J. 2013;12:291. doi: 10.1186/1475-2875-12-291 23968494
18. Okell LC, Griffin JT, Kleinschmidt I, Hollingsworth TD, Churcher TS, White MJ, et al. The potential contribution of mass treatment to the control of Plasmodium falciparum malaria. PLoS ONE. 2011;6(5):e20179. doi: 10.1371/journal.pone.0020179 21629651
19. Slater HC, Walker PG, Bousema T, Okell LC, Ghani AC. The potential impact of adding ivermectin to a mass treatment intervention to reduce malaria transmission: a modelling study. J Infect Dis. 2014;210(12):1972–80. doi: 10.1093/infdis/jiu351 24951826
20. Wenger EA, Eckhoff PA. A mathematical model of the impact of present and future malaria vaccines. Malar J. 2013;12:126. doi: 10.1186/1475-2875-12-126 23587051
21. Brady OJ, Godfray HC, Tatem AJ, Gething PW, Cohen JM, McKenzie FE, et al. Vectorial capacity and vector control: reconsidering sensitivity to parameters for malaria elimination. Trans R Soc Trop Med Hyg. 2016;110(2):107–17. doi: 10.1093/trstmh/trv113 26822603
22. Eckhoff P. Mathematical models of within-host and transmission dynamics to determine effects of malaria interventions in a variety of transmission settings. Am J Trop Med Hyg. 2013;88(5):817–27. doi: 10.4269/ajtmh.12-0007 23589530
23. Griffin JT, Bhatt S, Sinka ME, Gething PW, Lynch M, Patouillard E, et al. Potential for reduction of burden and local elimination of malaria by reducing Plasmodium falciparum malaria transmission: a mathematical modelling study. Lancet Infect Dis. 2016;16(4):465–72. doi: 10.1016/S1473-3099(15)00423-5 26809816
24. Lutambi AM, Chitnis N, Briet OJ, Smith TA, Penny MA. Clustering of vector control interventions has important consequences for their effectiveness: a modelling study. PLoS ONE. 2014;9(5):e97065. doi: 10.1371/journal.pone.0097065 24823656
25. Slater HC, Ross A, Ouedraogo AL, White LJ, Nguon C, Walker PG, et al. Assessing the impact of next-generation rapid diagnostic tests on Plasmodium falciparum malaria elimination strategies. Nature. 2015;528(7580):S94–101. doi: 10.1038/nature16040 26633771
26. Slater HC, Griffin JT, Ghani AC, Okell LC. Assessing the potential impact of artemisinin and partner drug resistance in sub-Saharan Africa. Malar J. 2016;15(1):10.
27. White MT, Griffin JT, Churcher TS, Ferguson NM, Basanez MG, Ghani AC. Modelling the impact of vector control interventions on Anopheles gambiae population dynamics. Parasit Vectors. 2011;4:153. doi: 10.1186/1756-3305-4-153 21798055
28. Crowell V, Briet OJ, Hardy D, Chitnis N, Maire N, Di Pasquale A, et al. Modelling the cost-effectiveness of mass screening and treatment for reducing Plasmodium falciparum malaria burden. Malar J. 2013;12:4. doi: 10.1186/1475-2875-12-4 23286228
29. MESA Track: Malaria Eradication Scientific Alliance; [updated 15 March 2016. Available from: http://www.malariaeradication.org/mesa-track
30. Maude RJ, Nguon C, Dondorp AM, White LJ, White NJ. The diminishing returns of atovaquone-proguanil for elimination of Plasmodium falciparum malaria: modelling mass drug administration and treatment. Malar J. 2014;13:380. doi: 10.1186/1475-2875-13-380 25249272
31. Maude RJ, Pontavornpinyo W, Saralamba S, Aguas R, Yeung S, Dondorp AM, et al. The last man standing is the most resistant: eliminating artemisinin-resistant malaria in Cambodia. Malaria Journal. 2009;8(1):31.
32. Maude RJ, Socheat D, Nguon C, Saroth P, Dara P, Li G, et al. Optimising strategies for Plasmodium falciparum malaria elimination in Cambodia: primaquine, mass drug administration and artemisinin resistance. PLoS ONE. 2012;7(5):e37166. doi: 10.1371/journal.pone.0037166 22662135
33. Silal SP, Little F, Barnes KI, White LJ. Predicting the impact of border control on malaria transmission: a simulated focal screen and treat campaign. Malar J. 2015;14:268. doi: 10.1186/s12936-015-0776-2 26164675
34. Silal SP, Little F, Barnes KI, White LJ. Hitting a moving target: A model for malaria elimination in the presence of population movement. PLoS ONE. 2015;10(12):e0144990. doi: 10.1371/journal.pone.0144990 26689547
35. White LJ, Maude RJ, Pongtavornpinyo W, Saralamba S, Aguas R, Van Effelterre T, et al. The role of simple mathematical models in malaria elimination strategy design. Malar J. 2009;8:212. doi: 10.1186/1475-2875-8-212 19747403
36. Penny MA, Verity R, Bever CA, Sauboin C, Galactionova K, Flasche S, et al. Public health impact and cost-effectiveness of the RTS,S/AS01 malaria vaccine: a systematic comparison of predictions from four mathematical models. Lancet. 2016;387(10016):367–75. doi: 10.1016/S0140-6736(15)00725-4 26549466
37. Bhatt S, Weiss DJ, Mappin B, Dalrymple U, Cameron E, Bisanzio D, et al. Coverage and system efficiencies of insecticide-treated nets in Africa from 2000 to 2017. Elife. 2015;4:e09672. doi: 10.7554/eLife.09672 26714109
38. Briet O, Hardy D, Smith TA. Importance of factors determining the effective lifetime of a mass, long-lasting, insecticidal net distribution: a sensitivity analysis. Malaria Journal. 2012;11(1):20.
39. Chitnis N, Schapira A, Smith T, Steketee R. Comparing the effectiveness of malaria vector-control interventions through a mathematical model. Am J Trop Med Hyg. 2010;83(2):230–40. doi: 10.4269/ajtmh.2010.09-0179 20682861
40. Griffin JT. The interaction between seasonality and pulsed interventions against malaria in their effects on the reproduction number. PLoS Comput Biol. 2015;11(1):e1004057. doi: 10.1371/journal.pcbi.1004057 25590612
41. Griffin JT, Hollingsworth TD, Okell LC, Churcher TS, White M, Hinsley W, et al. Reducing Plasmodium falciparum malaria transmission in Africa: a model-based evaluation of intervention strategies. PLoS Med. 2010;7(8):e1000324. doi: 10.1371/journal.pmed.1000324 20711482
42. Walker PG, Griffin JT, Ferguson NM, Ghani AC. Estimating the most efficient allocation of interventions to achieve reductions in Plasmodium falciparum malaria burden and transmission in Africa: a modelling study. Lancet Glob Health. 2016;4(7):e474–84. doi: 10.1016/S2214-109X(16)30073-0 27269393
43. Briet OJ, Penny MA. Repeated mass distributions and continuous distribution of long-lasting insecticidal nets: modelling sustainability of health benefits from mosquito nets, depending on case management. Malar J. 2013;12:401. doi: 10.1186/1475-2875-12-401 24200296
44. Brady OJ, Godfray HC, Tatem AJ, Gething PW, Cohen JM, McKenzie FE, et al. Adult vector control, mosquito ecology and malaria transmission. Int Health. 2015;7(2):121–9. doi: 10.1093/inthealth/ihv010 25733562
45. Eckhoff PA. A malaria transmission-directed model of mosquito life cycle and ecology. Malar J. 2011;10:303. doi: 10.1186/1475-2875-10-303 21999664
46. Killeen GF, Seyoum A, Gimnig JE, Stevenson JC, Drakeley CJ, Chitnis N. Made-to-measure malaria vector control strategies: rational design based on insecticide properties and coverage of blood resources for mosquitoes. Malaria Journal. 2014;13:146. doi: 10.1186/1475-2875-13-146 24739261
47. Okell LC, Drakeley CJ, Bousema T, Whitty CJ, Ghani AC. Modelling the impact of artemisinin combination therapy and long-acting treatments on malaria transmission intensity. PLoS Med. 2008;5(11):e226. doi: 10.1371/journal.pmed.0050226 19067479
48. Ross A, Maire N, Sicuri E, Smith T, Conteh L. Determinants of the cost-effectiveness of intermittent preventive treatment for malaria in infants and children. PLoS ONE. 2011;6(4):e18391. doi: 10.1371/journal.pone.0018391 21490967
49. Ross A, Penny M, Maire N, Studer A, Carneiro I, Schellenberg D, et al. Modelling the epidemiological impact of intermittent preventive treatment against malaria in infants. PLoS ONE. 2008;3(7):e2661. doi: 10.1371/journal.pone.0002661 18628828
50. Crowell V, Hardy D, Briet O, Chitnis N, Maire N, Smith T. Can we depend on case management to prevent re-establishment of P. falciparum malaria, after local interruption of transmission? Epidemics. 2012;4(1):1–8. doi: 10.1016/j.epidem.2011.10.003 22325009
51. Smith DL, Cohen JM, Chiyaka C, Johnston G, Gething PW, Gosling R, et al. A sticky situation: the unexpected stability of malaria elimination. Philos Trans R Soc Lond B Biol Sci. 2013;368(1623):20120145. doi: 10.1098/rstb.2012.0145 23798693
52. Cairns M, Ghani A, Okell L, Gosling R, Carneiro I, Anto F, et al. Modelling the protective efficacy of alternative delivery schedules for intermittent preventive treatment of malaria in infants and children. PLoS ONE. 2011;6(4):e18947. doi: 10.1371/journal.pone.0018947 21533088
53. Okell L, Slater H, Ghani A, P P-R, Smith TA, Chitnis N, et al. Consensus modelling evidence to support the design of mass drug administration programmes Geneva: WHO; 2015 [updated 14th March 2016. Available from: http://www.who.int/malaria/mpac/mpac-sept2015-consensus-modelling-mda.pdf
54. Stuckey EM, Miller JM, Littrell M, Chitnis N, Steketee R. Operational strategies of anti-malarial drug campaigns for malaria elimination in Zambia's southern province: a simulation study. Malar J. 2016;15(1):148.
55. Stuckey EM, Stevenson J, Galactionova K, Baidjoe AY, Bousema T, Odongo W, et al. Modeling the cost effectiveness of malaria control interventions in the highlands of western Kenya. PLoS ONE. 2014;9(10):e107700. doi: 10.1371/journal.pone.0107700 25290939
56. Eckhoff PA, Bever CA, Gerardin J, Wenger EA. Fun with maths: exploring implications of mathematical models for malaria eradication. Malar J. 2014;13:486. doi: 10.1186/1475-2875-13-486 25495423
57. Gerardin J, Eckhoff P, Wenger EA. Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination. BMC Infect Dis. 2015;15:144. doi: 10.1186/s12879-015-0887-y 25887935
58. Global Health Group at the University of California, Malaria Centre at the London School of Hygiene & Tropical Medicine. Single low-dose primaquine to interrupt P. falciparum transmission in Africa: a roadmap update and meeting summary 2014. Available from: http://www.shrinkingthemalariamap.org/sites/www.shrinkingthemalariamap.org/files/content/resource/attachment/London%20PQ%202016%20summary%20final%20for%20internet%209-12-16%20%25282%2529.pdf
59. Rao VB, Schellenberg D, Ghani AC. The potential impact of improving appropriate treatment for fever on malaria and non-malarial febrile illness management in under-5s: a decision-tree modelling approach. PLoS ONE. 2013;8(7):e69654. doi: 10.1371/journal.pone.0069654 23922770
60. Drake TL, Kyaw SS, Kyaw MP, Smithuis FM, Day NP, White LJ, et al. Cost effectiveness and resource allocation of Plasmodium falciparum malaria control in Myanmar: a modelling analysis of bed nets and community health workers. Malar J. 2015;14:376. doi: 10.1186/s12936-015-0886-x 26416075
61. Drake TL, Devine A, Yeung S, Day NP, White LJ, Lubell Y. Dynamic transmission economic evaluation of infectious disease interventions in low- and middle-income countries: A systematic literature review. Health Econ. 2016;25 Suppl 1:124–39.
62. Kyaw SS, Drake T, Thi A, Kyaw MP, Hlaing T, Smithuis FM, et al. Malaria community health workers in Myanmar: a cost analysis. Malar J. 2016;15(1):41.
63. Okell LC, Cairns M, Griffin JT, Ferguson NM, Tarning J, Jagoe G, et al. Contrasting benefits of different artemisinin combination therapies as first-line malaria treatments using model-based cost-effectiveness analysis. Nat Commun. 2014;5:5606. doi: 10.1038/ncomms6606 25425081
64. Hodel EM, Kay K, Hayes DJ, Terlouw DJ, Hastings IM. Optimizing the programmatic deployment of the anti-malarials artemether-lumefantrine and dihydroartemisinin-piperaquine using pharmacological modelling. Malar J. 2014;13:138. doi: 10.1186/1475-2875-13-138 24708571
65. Fernando SD, Navaratne CJ, Galappaththy GN, Abeyasinghe RR, Silva N, Wickermasinghe R. The importance of accuracy in diagnosis of positive malaria cases in a country progressing towards malaria elimination. J Glob Infect Dis. 2013;5(4):127–30. doi: 10.4103/0974-777X.121992 24672172
66. Mavandadi S, Feng S, Yu F, Dimitrov S, Nielsen-Saines K, Prescott WR, et al. A mathematical framework for combining decisions of multiple experts toward accurate and remote diagnosis of malaria using tele-microscopy. PLoS ONE. 2012;7(10):e46192. doi: 10.1371/journal.pone.0046192 23071544
67. McCarthy KA, Wenger EA, Huynh GH, Eckhoff PA. Calibration of an intrahost malaria model and parameter ensemble evaluation of a pre-erythrocytic vaccine. Malar J. 2015;14:6. doi: 10.1186/1475-2875-14-6 25563798
68. Smith T, Ross A, Maire N, Chitnis N, Studer A, Hardy D, et al. Ensemble modeling of the likely public health impact of a pre-erythrocytic malaria vaccine. PLoS Med. 2012;9(1):e1001157. doi: 10.1371/journal.pmed.1001157 22272189
69. White MT, Griffin JT, Riley EM, Drakeley CJ, Moorman AM, Sumba PO, et al. Efficacy model for antibody-mediated pre-erythrocytic malaria vaccines. Proc Biol Sci. 2011;278(1710):1298–305. doi: 10.1098/rspb.2010.1697 20943696
70. Diaz H, Ramirez AA, Olarte A, Clavijo C. A model for the control of malaria using genetically modified vectors. J Theor Biol. 2011;276(1):57–66. doi: 10.1016/j.jtbi.2011.01.053 21300074
71. Li J. Discrete-time models with mosquitoes carrying genetically-modified bacteria. Math Biosci. 2012;240(1):35–44. doi: 10.1016/j.mbs.2012.05.012 22771952
72. Legros M, Xu C, Okamoto K, Scott TW, Morrison AC, Lloyd AL, et al. Assessing the feasibility of controlling Aedes aegypti with transgenic methods: a model-based evaluation. PLoS ONE. 2012;7(12):e52235. doi: 10.1371/journal.pone.0052235 23284949
73. White MT, Smith DL. Synergism from combinations of infection-blocking malaria vaccines. Malar J. 2013;12:280. doi: 10.1186/1475-2875-12-280 23927630
74. WHO Malaria Policy Advisory Committee Secretariat. Malaria Policy Advisory Committee to the WHO: conclusions and recommendations of eighth biannual meeting (September 2015). Malar J. 2016;15(1):117.
75. Guyant P, Corbel V, Guerin PJ, Lautissier A, Nosten F, Boyer S, et al. Past and new challenges for malaria control and elimination: the role of operational research for innovation in designing interventions. Malar J. 2015;14:279. doi: 10.1186/s12936-015-0802-4 26185098
76. Hsiang MS, Hwang J, Tao AR, Liu Y, Bennett A, Shanks GD, et al. Mass drug administration for the control and elimination of Plasmodium vivax malaria: an ecological study from Jiangsu province, China. Malar J. 2013;12:383. doi: 10.1186/1475-2875-12-383 24175930
77. Kiware SS, Chitnis N, Devine GJ, Moore SJ, Majambere S, Killeen GF. Biologically meaningful coverage indicators for eliminating malaria transmission. Biol Lett. 2012;8(5):874–7. doi: 10.1098/rsbl.2012.0352 22647930
78. Poirot E, Skarbinski J, Sinclair D, Kachur SP, Slutsker L, Hwang J. Mass drug administration for malaria. Cochrane Database Syst Rev. 2013;12:CD008846.
79. Rosas-Aguirre A, Erhart A, Llanos-Cuentas A, Branch O, Berkvens D, Abatih E, et al. Modelling the potential of focal screening and treatment as elimination strategy for Plasmodium falciparum malaria in the Peruvian Amazon Region. Parasit Vectors. 2015;8:261. doi: 10.1186/s13071-015-0868-4 25948081
80. Eisele TP, Silumbe K, Finn T, Chalwe V, Kamuliwo M, Hamainza B, et al. Assessing the effectiveness of household-level focal mass drug administration and community-wide mass drug administration for reducing malaria parasite infection prevalence and incidence in Southern Province, Zambia: study protocol for a community randomized controlled trial. Trials. 2015;16:347. doi: 10.1186/s13063-015-0862-3 26268804
81. Alegana VA, Wright JA, Nahzat SM, Butt W, Sediqi AW, Habib N, et al. Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006–2009. PLoS ONE. 2014;9(7).
82. Chen Z, Shi L, Zhou XN, Xia ZG, Bergquist R, Jiang QW. Elimination of malaria due to Plasmodium vivax in central part of the People's Republic of China: analysis and prediction based on modelling. Geospatial Health. 2014;9(1):169–77. doi: 10.4081/gh.2014.14 25545934
83. Galappaththy Gawrie NL, Tharyan P, Kirubakaran R. Primaquine for preventing relapse in people with Plasmodium vivax malaria treated with chloroquine. Cochrane Database of Systematic Reviews [Internet]. 2013; (10). Available from: http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD004389.pub3/abstract
84. Lindsay SW, Hole DG, Hutchinson RA, Richards SA, Willis SG. Assessing the future threat from vivax malaria in the United Kingdom using two markedly different modelling approaches. Malaria Journal. 2010;9.
85. Roy M, Bouma MJ, Ionides EL, Dhiman RC, Pascual M. The potential elimination of Plasmodium vivax malaria by relapse treatment: insights from a transmission model and surveillance data from NW India. PLoS Negl Trop Dis. 2013;7(1):e1979. doi: 10.1371/journal.pntd.0001979 23326611
86. Shi B, Liu J, Zhou XN, Yang GJ. Inferring Plasmodium vivax transmission networks from tempo-spatial surveillance data. PLoS Negl Trop Dis. 2014;8(2):e2682. doi: 10.1371/journal.pntd.0002682 24516684
87. Robinson LJ, Wampfler R, Betuela I, Karl S, White MT, Li Wai Suen CS, et al. Strategies for understanding and reducing the Plasmodium vivax and Plasmodium ovale hypnozoite reservoir in Papua New Guinean children: a randomised placebo-controlled trial and mathematical model. PLoS Med. 2015;12(10):e1001891. doi: 10.1371/journal.pmed.1001891 26505753
88. White MT, Karl S, Battle KE, Hay SI, Mueller I, Ghani AC. Modelling the contribution of the hypnozoite reservoir to Plasmodium vivax transmission. Elife. 2014;3:e04692.
89. Abdullahi MB, Hasan YA, Abdullah FA. Optimal control of Plasmodium knowlesi malaria in human and macaques. British Journal of Mathematics & Computer Science. 2014;4(2):271–87.
90. Abdullahi MB, Hasan YA, Abdullah FA. Optimal strategy for controlling the spread of Plasmodium knowlesi malaria: Treatment and culling. AIP Conference Proceedings. 2015;1660(1):050005.
91. Adekunle AI, Pinkevych M, McGready R, Luxemburger C, White LJ, Nosten F, et al. Modeling the dynamics of Plasmodium vivax infection and hypnozoite reactivation in vivo. PLoS Negl Trop Dis. 2015;9(3):e0003595. doi: 10.1371/journal.pntd.0003595 25780913
92. Qi Q, Guerra CA, Moyes CL, Elyazar IR, Gething PW, Hay SI, et al. The effects of urbanization on global Plasmodium vivax malaria transmission. Malar J. 2012;11:403. doi: 10.1186/1475-2875-11-403 23217010
93. White MT, Shirreff G, Karl S, Ghani AC, Mueller I. Variation in relapse frequency and the transmission potential of Plasmodium vivax malaria. Proc Biol Sci. 2016;283(1827).
94. Ross A, Koepfli C, Schoepflin S, Timinao L, Siba P, Smith T, et al. The incidence and differential seasonal patterns of Plasmodium vivax primary infections and relapses in a cohort of children in Papua New Guinea. PLoS Negl Trop Dis. 2016;10(5):e0004582. doi: 10.1371/journal.pntd.0004582 27144482
95. Imai N, White MT, Ghani AC, Drakeley CJ. Transmission and control of Plasmodium knowlesi: a mathematical modelling study. PLoS Negl Trop Dis. 2014;8(7):e2978. doi: 10.1371/journal.pntd.0002978 25058400
96. Aguas R, Ferreira MU, Gomes MG. Modeling the effects of relapse in the transmission dynamics of malaria parasites. J Parasitol Res. 2012;2012:921715. doi: 10.1155/2012/921715 21966590
97. Pampana E. Textbook of Malaria Eradication. Oxford: Oxford University Press; 1969.
98. Ashton RA, Kefyalew T, Rand A, Sime H, Assefa A, Mekasha A, et al. Geostatistical modeling of malaria endemicity using serological indicators of exposure collected through school surveys. American Journal of Tropical Medicine and Hygiene. 2015;93 (1):168–77. doi: 10.4269/ajtmh.14-0620 25962770
99. Bousema T, Drakeley C, Gesase S, Hashim R, Magesa S, Mosha F, et al. Identification of hot spots of malaria transmission for targeted malaria control. J Infect Dis. 2010;201(11):1764–74. doi: 10.1086/652456 20415536
100. Mosha JF, Sturrock HJ, Greenwood B, Sutherland CJ, Gadalla NB, Atwal S, et al. Hot spot or not: a comparison of spatial statistical methods to predict prospective malaria infections. Malar J. 2014;13:53. doi: 10.1186/1475-2875-13-53 24517452
101. Pothin E, Ferguson NM, Drakeley CJ, Ghani AC. Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models. Malar J. 2016;15(1):79.
102. malERA Refresh Consultative Panel on Characterising the Reservoir and Measuring Transmission. malERA: An updated research agenda for characterising the reservoir and measuring transmission in malaria elimination and eradication. PLoS Med. 2017;14(11):e1002452. doi: 10.1371/journal.pmed.1002452
103. Hustedt J, Canavati SE, Rang C, Ashton RA, Khim N, Berne L, et al. Reactive case-detection of malaria in Pailin Province, Western Cambodia: lessons from a year-long evaluation in a pre-elimination setting. Malar J. 2016;15(1):132.
104. Larsen DA, Chisha Z, Winters B, Mwanza M, Kamuliwo M, Mbwili C, et al. Malaria surveillance in low-transmission areas of Zambia using reactive case detection. Malar J. 2015;14(1):465.
105. Littrell M, Sow GD, Ngom A, Ba M, Mboup BM, Dieye Y, et al. Case investigation and reactive case detection for malaria elimination in northern Senegal. Malar J. 2013;12:331. doi: 10.1186/1475-2875-12-331 24044506
106. van Eijk AM, Ramanathapuram L, Sutton PL, Kanagaraj D, Sri Lakshmi Priya G, Ravishankaran S, et al. What is the value of reactive case detection in malaria control? A case-study in India and a systematic review. Malar J. 2016;15(1):67.
107. Zhou SS, Zhang SS, Zhang L, Rietveld AE, Ramsay AR, Zachariah R, et al. China's 1-3-7 surveillance and response strategy for malaria elimination: Is case reporting, investigation and foci response happening according to plan? Infect Dis Poverty. 2015;4:55. doi: 10.1186/s40249-015-0089-2 26654106
108. Cohen JM, Smith DL, Cotter C, Ward A, Yamey G, Sabot OJ, et al. Malaria resurgence: a systematic review and assessment of its causes. Malar J. 2012;11:122. doi: 10.1186/1475-2875-11-122 22531245
109. Reiner RC, Le Menach A, Kunene S, Ntshalintshali N, Hsiang MS, Perkins TA, et al. Mapping residual transmission for malaria elimination. Elife. 2015;4:e09520. doi: 10.7554/eLife.09520 26714110
110. Hemingway J, Ranson H, Magill A, Kolaczinski J, Fornadel C, Gimnig J, et al. Averting a malaria disaster: will insecticide resistance derail malaria control? Lancet. 2016;387:1785–8. doi: 10.1016/S0140-6736(15)00417-1 26880124
111. World Health Organization. Emergency response to artemisinin resistance in the Greater Mekong subregion. Regional framework for action 2013–2015 Geneva: WHO; 2013. Available from: http://www.who.int/malaria/publications/atoz/9789241505321/en/.
112. malERA Refresh Consultative Panel on Insecticide and Drug Resistance. malERA: An updated research agenda for insecticide and drug resistance in malaria elimination and eradication. PLoS Med. 2017;14(11):e1002450. doi: 10.1371/journal.pmed.1002450
113. Briet OJ, Penny MA, Hardy D, Awolola TS, Van Bortel W, Corbel V, et al. Effects of pyrethroid resistance on the cost effectiveness of a mass distribution of long-lasting insecticidal nets: a modelling study. Malar J. 2013;12:77. doi: 10.1186/1475-2875-12-77 23442575
114. Killeen GF, Chitnis N. Potential causes and consequences of behavioural resilience and resistance in malaria vector populations: a mathematical modelling analysis. Malar J. 2014;13:97. doi: 10.1186/1475-2875-13-97 24629066
115. Lubell Y, Dondorp A, Guerin PJ, Drake T, Meek S, Ashley E, et al. Artemisinin resistance—modelling the potential human and economic costs. Malar J. 2014;13:452. doi: 10.1186/1475-2875-13-452 25418416
116. Griffin JT, Cairns M, Ghani AC, Roper C, Schellenberg D, Carneiro I, et al. Protective efficacy of intermittent preventive treatment of malaria in infants (IPTi) using sulfadoxine-pyrimethamine and parasite resistance. PLoS ONE. 2010;5(9):e12618. doi: 10.1371/journal.pone.0012618 20838642
117. Hlaing T, Wai KT, Oo T, Sint N, Min T, Myar S, et al. Mobility dynamics of migrant workers and their socio-behavioral parameters related to malaria in Tier II, Artemisinin Resistance Containment Zone, Myanmar. BMC Public Health. 2015;15:886. doi: 10.1186/s12889-015-2241-0 26370297
118. Malisa AL, Pearce RJ, Abdulla S, Mshinda H, Kachur PS, Bloland P, et al. Drug coverage in treatment of malaria and the consequences for resistance evolution—evidence from the use of sulphadoxine/pyrimethamine. Malar J. 2010;9:190. doi: 10.1186/1475-2875-9-190 20602754
119. Winter K, Hastings IM. Development, evaluation, and application of an in silico model for antimalarial drug treatment and failure. Antimicrob Agents Chemother. 2011;55(7):3380–92. doi: 10.1128/AAC.01712-10 21537019
120. Grist EP, Flegg JA, Humphreys G, Mas IS, Anderson TJ, Ashley EA, et al. Optimal health and disease management using spatial uncertainty: a geographic characterization of emergent artemisinin-resistant Plasmodium falciparum distributions in Southeast Asia. Int J Health Geogr. 2016;15(1):37. doi: 10.1186/s12942-016-0064-6 27776514
121. Corbel V, Akogbeto M, Damien GB, Djenontin A, Chandre F, Rogier C, et al. Combination of malaria vector control interventions in pyrethroid resistance area in Benin: a cluster randomised controlled trial. Lancet Infect Dis. 2012;12(8):617–26. doi: 10.1016/S1473-3099(12)70081-6 22682536
122. Menger DJ, Omusula P, Holdinga M, Homan T, Carreira AS, Vandendaele P, et al. Field evaluation of a push-pull system to reduce malaria transmission. PLoS ONE. 2015;10(4):e0123415. doi: 10.1371/journal.pone.0123415 25923114
123. Tchuenche JM, Chiyaka C, Chan D, Matthews A, Mayer G. A mathematical model for antimalarial drug resistance. Math Med Biol. 2011;28(4):335–55. doi: 10.1093/imammb/dqq017 20884768
124. Kunkel A, Colijn C, Lipsitch M, Cohen T. How could preventive therapy affect the prevalence of drug resistance? Causes and consequences. Philos Trans R Soc Lond B Biol Sci. 2015;370(1670):20140306. doi: 10.1098/rstb.2014.0306 25918446
125. Barbosa S, Hastings IM. The importance of modelling the spread of insecticide resistance in a heterogeneous environment: the example of adding synergists to bed nets. Malar J. 2012;11:258. doi: 10.1186/1475-2875-11-258 22856525
126. Eckhoff PA. Malaria parasite diversity and transmission intensity affect development of parasitological immunity in a mathematical model. Malar J. 2012;11:419. doi: 10.1186/1475-2875-11-419 23241282
127. Fowkes FJ, Boeuf P, Beeson JG. Immunity to malaria in an era of declining malaria transmission. Parasitology. 2016;143(2):139–53. doi: 10.1017/S0031182015001249 26741253
128. Griffin JT, Ferguson NM, Ghani AC. Estimates of the changing age-burden of Plasmodium falciparum malaria disease in sub-Saharan Africa. Nat Commun. 2014;5:3136. doi: 10.1038/ncomms4136 24518518
129. Griffin JT, Hollingsworth TD, Reyburn H, Drakeley CJ, Riley EM, Ghani AC. Gradual acquisition of immunity to severe malaria with increasing exposure. Proc Biol Sci. 2015;282(1801):20142657. doi: 10.1098/rspb.2014.2657 25567652
130. Eckhoff P. P. falciparum infection durations and infectiousness are shaped by antigenic variation and innate and adaptive host immunity in a mathematical model. PLoS ONE. 2012;7(9):e44950. doi: 10.1371/journal.pone.0044950 23028698
131. Smith T, Ross A, Maire N, Rogier C, Trape JF, Molineaux L. An epidemiologic model of the incidence of acute illness in Plasmodium falciparum malaria. Am J Trop Med Hyg. 2006;75(2 Suppl):56–62.
132. Elbadry MA, Al-Khedery B, Tagliamonte MS, Yowell CA, Raccurt CP, Existe A, et al. High prevalence of asymptomatic malaria infections: a cross-sectional study in rural areas in six departments in Haiti. Malar J. 2015;14:510. doi: 10.1186/s12936-015-1051-2 26689195
133. Alimi TO, Fuller DO, Qualls WA, Herrera SV, Arevalo-Herrera M, Quinones ML, et al. Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population. Parasit Vectors. 2015;8:431. doi: 10.1186/s13071-015-1033-9 26289677
134. Baeza A, Bouma MJ, Dhiman R, Pascual M. Malaria control under unstable dynamics: reactive vs. climate-based strategies. Acta Trop. 2014;129:42–51. doi: 10.1016/j.actatropica.2013.04.001 23567551
135. Caminade C, Kovats S, Rocklov J, Tompkins AM, Morse AP, Colon-Gonzalez FJ, et al. Impact of climate change on global malaria distribution. Proc Natl Acad Sci U S A. 2014;111(9):3286–91. doi: 10.1073/pnas.1302089111 24596427
136. Caruana CM. A new breed of model: estimating the impact of climate change on malaria transmission. Environ Health Perspect. 2013;121(10):A310. doi: 10.1289/ehp.121-A310 24218662
137. Christiansen-Jucht C, Erguler K, Shek CY, Basanez MG, Parham PE. Modelling Anopheles gambiae s.s. population dynamics with temperature- and age-dependent survival. Int J Environ Res Public Health. 2015;12(6):5975–6005. doi: 10.3390/ijerph120605975 26030468
138. Khormi HM, Kumar L. Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia. Geospat Health. 2016;11(3):416. doi: 10.4081/gh.2016.416 27903054
139. Laporta GZ, Linton YM, Wilkerson RC, Bergo ES, Nagaki SS, Sant'Ana DC, et al. Malaria vectors in South America: current and future scenarios. Parasit Vectors. 2015;8:426. doi: 10.1186/s13071-015-1038-4 26283539
140. Leedale J, Tompkins AM, Caminade C, Jones AE, Nikulin G, Morse AP. Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty. Geospat Health. 2016;11(1 Suppl):393.
141. Mweya CN, Kimera SI, Stanley G, Misinzo G, Mboera LE. Climate change influences potential distribution of infected Aedes aegypti co-occurrence with dengue epidemics risk areas in tanzania. PLoS ONE. 2016;11(9):e0162649. doi: 10.1371/journal.pone.0162649 27681327
142. Ngarakana-Gwasira ET, Bhunu CP, Masocha M, Mashonjowa E. Assessing the role of climate change in malaria transmission in Africa. Malar Res Treat. 2016;2016:7104291. doi: 10.1155/2016/7104291 27066290
143. Onyango EA, Sahin O, Awiti A, Chu C, Mackey B. An integrated risk and vulnerability assessment framework for climate change and malaria transmission in East Africa. Malar J. 2016;15(1):551. doi: 10.1186/s12936-016-1600-3 27835976
144. Pascual M. Climate and population immunity in malaria dynamics: Harnessing information from endemicity gradients. Trends Parasitol. 2015;31(11):532–4. doi: 10.1016/j.pt.2015.08.009 26422773
145. Ryan SJ, McNally A, Johnson LR, Mordecai EA, Ben-Horin T, Paaijmans K, et al. Mapping physiological suitability limits for malaria in Africa under climate change. Vector Borne Zoonotic Dis. 2015;15(12):718–25. doi: 10.1089/vbz.2015.1822 26579951
146. Salahi-Moghaddam A, Khoshdel A, Dalaei H, Pakdad K, Nutifafa GG, Sedaghat MM. Spatial changes in the distribution of malaria vectors during the past 5 decades in Iran. Acta Trop. 2017;166:45–53. doi: 10.1016/j.actatropica.2016.11.001 27826012
147. Song Y, Ge Y, Wang J, Ren Z, Liao Y, Peng J. Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050. Malar J. 2016;15(1):345. doi: 10.1186/s12936-016-1395-2 27387921
148. Tompkins AM, Caporaso L. Assessment of malaria transmission changes in Africa, due to the climate impact of land use change using Coupled Model Intercomparison Project Phase 5 earth system models. Geospat Health. 2016;11(1 Suppl):380.
149. Tonnang HE, Tchouassi DP, Juarez HS, Igweta LK, Djouaka RF. Zoom in at African country level: potential climate induced changes in areas of suitability for survival of malaria vectors. Int J Health Geogr. 2014;13:12. doi: 10.1186/1476-072X-13-12 24885061
150. Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J. The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework. Proc Natl Acad Sci U S A. 2014;111(9):3228–32. doi: 10.1073/pnas.1312330110 24344316
151. Yamana TK, Eltahir EA. Projected impacts of climate change on environmental suitability for malaria transmission in West Africa. Environ Health Perspect. 2013;121(10):1179–86. doi: 10.1289/ehp.1206174 24043443
152. Bakare E, Nwozo C. On the mathematical analysis of the influence of chemoprophylaxis on the malaria epidemic model. International Journal of Contemporary Mathematical Sciences. 2016;11:45–63.
153. Kyaw SS, Drake T, Ruangveerayuth R, Chierakul W, White NJ, Newton PN, et al. Cost of treating inpatient falciparum malaria on the Thai-Myanmar border. Malar J. 2014;13:416. doi: 10.1186/1475-2875-13-416 25351915
154. Labadin J, Kon M, Juan S. Deterministic malaria transmission model with acquired immunity WCECS 2009, October 20–22, 2009, San Francisco, USA2009. Available from: http://www.iaeng.org/publication/WCECS2009/WCECS2009_pp779-784.pdf
155. Hagenlocher M, Castro MC. Mapping malaria risk and vulnerability in the United Republic of Tanzania: a spatial explicit model. Popul Health Metr. 2015;13(1):2. doi: 10.1186/s12963-015-0036-2 25674040
156. Ranjbar M, Shoghli A, Kolifarhood G, Tabatabaei SM, Amlashi M, Mohammadi M. Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks. Malar J. 2016;15(1):138.
157. Acevedo MA, Prosper O, Lopiano K, Ruktanonchai N, Caughlin TT, Martcheva M, et al. Spatial heterogeneity, host movement and mosquito-borne disease transmission. PLoS ONE. 2015;10(6):e0127552. doi: 10.1371/journal.pone.0127552 26030769
158. Bomblies A. Agent-based modeling of malaria vectors: the importance of spatial simulation. Parasit Vectors. 2014;7:308. doi: 10.1186/1756-3305-7-308 24992942
159. Pindolia DK, Garcia AJ, Huang Z, Fik T, Smith DL, Tatem AJ. Quantifying cross-border movements and migrations for guiding the strategic planning of malaria control and elimination. Malar J. 2014;13:169. doi: 10.1186/1475-2875-13-169 24886389
160. Smith DL, Perkins TA, Reiner RC Jr., 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(4):185–97. doi: 10.1093/trstmh/tru026 24591453
161. Tatem AJ, Huang Z, Narib C, Kumar U, Kandula D, Pindolia DK, et al. Integrating rapid risk mapping and mobile phone call record data for strategic malaria elimination planning. Malar J. 2014;13:52. doi: 10.1186/1475-2875-13-52 24512144
162. Blanas DA, Ndiaye Y, MacFarlane M, Manga I, Siddiqui A, Velez O, et al. Health worker perceptions of integrating mobile phones into community case management of malaria in Saraya, Senegal. Int Health. 2015;7(3):176–82. doi: 10.1093/inthealth/ihu075 25316707
163. Ruktanonchai NW, Bhavnani D, Sorichetta A, Bengtsson L, Carter KH, Cordoba RC, et al. Census-derived migration data as a tool for informing malaria elimination policy. Malar J. 2016;15(1):273. doi: 10.1186/s12936-016-1315-5 27169470
164. Tompkins AM, McCreesh N. Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model. Geospat Health. 2016;11(1 Suppl):408.
165. Danis K, Lenglet A, Tseroni M, Baka A, Tsiodras S, Bonovas S. Malaria in Greece: historical and current reflections on a re-emerging vector borne disease. Travel Med Infect Dis. 2013;11(1):8–14. doi: 10.1016/j.tmaid.2013.01.001 23434287
166. Miguel RB, Peiter PC, de Albuquerque H, Coura JR, Moza PG, Costa Ade P, et al. Malaria in the state of Rio de Janeiro, Brazil, an Atlantic Forest area: an assessment using the health surveillance service. Mem Inst Oswaldo Cruz. 2014;109(5):634–40. doi: 10.1590/0074-0276130558 25185004
167. Dharmawardena P, Premaratne RG, Gunasekera WM, Hewawitarane M, Mendis K, Fernando D. Characterization of imported malaria, the largest threat to sustained malaria elimination from Sri Lanka. Malar J. 2015;14:177. doi: 10.1186/s12936-015-0697-0 25902716
168. Wang D, Li S, Cheng Z, Xiao N, Cotter C, Hwang J, et al. Transmission risk from imported Plasmodium vivax malaria in the China-Myanmar border region. Emerg Infect Dis. 2015;21(10):1861–4. doi: 10.3201/eid2110.150679 26401843
169. Ren Z, Wang D, Ma A, Hwang J, Bennett A, Sturrock HJ, et al. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination. Sci Rep. 2016;6:20604. doi: 10.1038/srep20604 26868185
170. Noor AM, Uusiku P, Kamwi RN, Katokele S, Ntomwa B, Alegana VA, et al. The receptive versus current risks of Plasmodium falciparum transmission in northern Namibia: implications for elimination. BMC Infect Dis. 2013;13:184. doi: 10.1186/1471-2334-13-184 23617955
171. Shahandeh K, Basseri HR, Sharifzadeh Y. An application of cultural model to assess and compare malaria prevention among Afghani migrant and Baluchi resident in the endemic area, southeastern Iran. J Immigr Minor Health. 2014;16(1):102–10. doi: 10.1007/s10903-013-9850-4 23775110
172. Gomes E, Capinha C, Rocha J, Sousa C. Mapping risk of malaria transmission in mainland Portugal using a mathematical modelling approach. PLoS ONE. 2016;11(11):e0164788. doi: 10.1371/journal.pone.0164788 27814371
173. Ranjbar M, Shoghli A, Kolifarhood G, Tabatabaei SM, Amlashi M, Mohammadi M. Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks. Malar J. 2016;15:138. doi: 10.1186/s12936-016-1192-y 26935846
174. Cohen JM, Ernst KC, Lindblade KA, Vulule JM, John CC, Wilson ML. Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands. Malar J. 2010;9:328. doi: 10.1186/1475-2875-9-328 21080943
175. Tatarsky A, Aboobakar S, Cohen JM, Gopee N, Bheecarry A, Moonasar D, et al. Preventing the reintroduction of malaria in Mauritius: a programmatic and financial assessment. PLoS ONE. 2011;6(9):e23832. doi: 10.1371/journal.pone.0023832 21912645
176. Durnez L, Coosemans M. Residual transmission of malaria: an old issue for new approaches: InTech; 2013. Available from: http://www.intechopen.com/books/anopheles-mosquitoes-new-insights-into-malaria-vectors/residual-transmission-of-malaria-an-old-issue-for-new-approaches
177. Lloyd AL, Zhang J, Root AM. Stochasticity and heterogeneity in host-vector models. J R Soc Interface. 2007;4(16):851–63. doi: 10.1098/rsif.2007.1064 17580290
178. Vazquez-Prokopec GM, Perkins TA, Waller LA, Lloyd AL, Reiner RC Jr., Scott TW, et al. Coupled heterogeneities and their impact on parasite transmission and control. Trends Parasitol. 2016;32(5):356–67. doi: 10.1016/j.pt.2016.01.001 26850821
179. Rao VB, Schellenberg D, Ghani AC. Overcoming health systems barriers to successful malaria treatment. Trends Parasitol. 2013;29(4):164–80. doi: 10.1016/j.pt.2013.01.005 23415933
180. Cohen JM, Sabot O, Sabot K, Gordon M, Gross I, Bishop D, et al. A pharmacy too far? Equity and spatial distribution of outcomes in the delivery of subsidized artemisinin-based combination therapies through private drug shops. BMC Health Serv Res. 2010;10 Suppl 1:S6.
181. Perkins TA, Scott TW, Le Menach A, Smith DL. Heterogeneity, mixing, and the spatial scales of mosquito-borne pathogen transmission. PLoS Comput Biol. 2013;9(12):e1003327. doi: 10.1371/journal.pcbi.1003327 24348223
182. Eckhoff P, Bever CA, Gerardin J, Wenger E, Smith D. From puddles to planet: Modeling approaches to vector-borne diseases at varying resolution and scale. Current Opinion in Insect Science. 2015;10:118–23.
183. Moonasar D, Maharaj R, Kunene S, Candrinho B, Saute F, Ntshalintshali N, et al. Towards malaria elimination in the MOSASWA (Mozambique, South Africa and Swaziland) region. Malar J. 2016;15(1):419. doi: 10.1186/s12936-016-1470-8 27538990
184. Raman J, Morris N, Frean J, Brooke B, Blumberg L, Kruger P, et al. Reviewing South Africa's malaria elimination strategy (2012–2018): progress, challenges and priorities. Malar J. 2016;15(1):438. doi: 10.1186/s12936-016-1497-x 27567642
185. Sturrock HJ, Roberts KW, Wegbreit J, Ohrt C, Gosling RD. Tackling imported malaria: an elimination endgame. Am J Trop Med Hyg. 2015;93(1):139–44. doi: 10.4269/ajtmh.14-0256 26013369
186. Wangdi K, Gatton ML, Kelly GC, Clements AC. Cross-border malaria: a major obstacle for malaria elimination. Adv Parasitol. 2015;89:79–107. doi: 10.1016/bs.apar.2015.04.002 26003036
187. Ferreira MU, Castro MC. Challenges for malaria elimination in Brazil. Malar J. 2016;15(1):284. doi: 10.1186/s12936-016-1335-1 27206924
188. Gryseels C, Peeters Grietens K, Dierickx S, Xuan XN, Uk S, Bannister-Tyrrell M, et al. High mobility and low use of malaria preventive measures among the Jarai male youth along the Cambodia-Vietnam border. Am J Trop Med Hyg. 2015;93(4):810–8. doi: 10.4269/ajtmh.15-0259 26283747
189. Hu Y, Zhou G, Ruan Y, Lee MC, Xu X, Deng S, et al. Seasonal dynamics and microgeographical spatial heterogeneity of malaria along the China-Myanmar border. Acta Trop. 2016;157:12–9. doi: 10.1016/j.actatropica.2016.01.022 26812008
190. Wangdi K, Banwell C, Gatton ML, Kelly GC, Namgay R, Clements AC. Development and evaluation of a spatial decision support system for malaria elimination in Bhutan. Malar J. 2016;15(1):180.
191. Bi Y, Hu W, Yang H, Zhou XN, Yu W, Guo Y, et al. Spatial patterns of malaria reported deaths in Yunnan Province, China. Am J Trop Med Hyg. 2013;88(3):526–35. doi: 10.4269/ajtmh.2012.12-0217 23269660
192. Lyttleton C. Deviance and resistance: Malaria elimination in the greater Mekong subregion. Soc Sci Med. 2016;150:144–52. doi: 10.1016/j.socscimed.2015.12.033 26751710
193. Wang RB, Dong JQ, Xia ZG, Cai T, Zhang QF, Zhang Y, et al. Lessons on malaria control in the ethnic minority regions in Northern Myanmar along the China border, 2007–2014. Infect Dis Poverty. 2016;5(1):95. doi: 10.1186/s40249-016-0191-0 27716435
194. Kanyangarara M, Mamini E, Mharakurwa S, Munyati S, Gwanzura L, Kobayashi T, et al. Individual- and household-level risk factors associated with malaria in Mutasa district, Zimbabwe: a serial cross-sectional study. Am J Trop Med Hyg. 2016;95(1):133–40. doi: 10.4269/ajtmh.15-0847 27114289
195. Zhang Q, Sun J, Zhang Z, Geng Q, Lai S, Hu W, et al. Risk assessment of malaria in land border regions of China in the context of malaria elimination. Malar J. 2016;15(1):546. doi: 10.1186/s12936-016-1590-1 27825379
Štítky
Interné lekárstvoČlánok vyšiel v časopise
PLOS Medicine
2017 Číslo 11
- Statiny indukovaná myopatie: Jak na diferenciální diagnostiku?
- MUDr. Dana Vondráčková: Hepatopatie sú pri liečbe metamizolom väčším strašiakom ako agranulocytóza
- Vztah mezi statiny a rizikem vzniku nádorových onemocnění − metaanalýza
- Nech brouka žít… Ať žije astma!
- Parazitičtí červi v terapii Crohnovy choroby a dalších zánětlivých autoimunitních onemocnění
Najčítanejšie v tomto čísle
- Postmenopausal hormone therapy and risk of stroke: A pooled analysis of data from population-based cohort studies
- HIV pre-exposure prophylaxis and early antiretroviral treatment among female sex workers in South Africa: Results from a prospective observational demonstration project
- Extensive virologic and immunologic characterization in an HIV-infected individual following allogeneic stem cell transplant and analytic cessation of antiretroviral therapy: A case study
- Bioequivalence between innovator and generic tacrolimus in liver and kidney transplant recipients: A randomized, crossover clinical trial