Understanding the importance of spatial correlation in identifying spatio-temporal variation of disease risk, in the case of malaria risk mapping in southern Ethiopia

Scientific African - Tập 22 - Trang e01926 - 2023
Yonas Shuke kitawa1, Olatunji Johnson2, Emanuele Giorgi3, Zeytu Gashaw Asfaw4
1Department of Statistics, College of Natural and Computational Science, Hawassa University, Hawassa, Ethiopia
2Department of Mathematics, University of Manchester, UK
3CHICAS, Lancaster Medical School, Lancaster University, Lancaster, UK
4Department of Bio-statistics and Epidemiology, School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia

Tài liệu tham khảo

Anderson, 2014, Identifying clusters in Bayesian disease mapping, Biostatistics, 15, 457, 10.1093/biostatistics/kxu005 Diggle, 2016, Model-based geostatistics for prevalence mapping in low-resource settings, Am. Stat. Assoc., 111, 1096, 10.1080/01621459.2015.1123158 WHO, 2019 Wakefield, 2007, Disease mapping and spatial regression with count data, Biostatistics, 8, 158, 10.1093/biostatistics/kxl008 Bhatt, 2015, The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015, Nature, 526, 207, 10.1038/nature15535 Weiss, 2019, Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000-17. A spatial and temporal modelling study, Lancet, 394, 322, 10.1016/S0140-6736(19)31097-9 WHO, 2020 Yeshiwondim, 2009, Spatial analysis of malaria incidence at the village level in areas with unstable transmission in Ethiopia, Int. J. Health Geogr., 8 Taffese, 2018, Malaria epidemiology and interventions in Ethiopia from 2001 to 2016, Infect. Dis. Poverty, 7 Girum, 2021, Burden of malaria in Ethiopia, 2000–2016: Findings from the global health estimates 2016, Trop. Dis. Travel Med. Vaccines, 5 Rodo, 2021, Malaria trends in Ethiopian highlands track the 2000 ’slowdown’ in global warming., Nature Commun., 12 Bivand, 2015 Illian, 2012, A toolbox for fitting complex spatial point process models using Integrated Nested Laplace Approximation (INLA), Ann. Appl. Stat., 6, 1499, 10.1214/11-AOAS530 Diggle, 2019 Christensen, 2004, Monte Carlo maximum likelihood in model-based geostatistics, Comput. Graph. Stat., 13, 702, 10.1198/106186004X2525 Joe, 2008, Accuracy of Laplace approximation for discrete response mixed models, Comput. Statist. Data Anal., 52, 5066, 10.1016/j.csda.2008.05.002 Besag, 1974, Spatial interaction and the statistical analysis of lattice systems, J. R. Stat. Soc. Ser. B Stat. Methodol., 36, 192 Diggle, 2013, Spatial and spatio-temporal log-Gaussian Cox processes: Extending the geostatistical paradigm, Statist. Sci., 28, 542, 10.1214/13-STS441 Kitawa, 2023, Space-time modelling of monthly malaria incidence for seasonal associated drivers and early epidemic detection in southern Ethiopia, Malar J., 22 Midekisa, 2012, Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia, Malar. J., 11 Colborn, 2018, Spatio-temporal modelling of weekly malaria incidence in children under 5 for early epidemic detection in mozambique, Sci. Rep., 8, 1, 10.1038/s41598-018-27537-4 Rushworth, 2017, An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk, R. Stat. Soc. C, 66, 141, 10.1111/rssc.12155 Besag, 1991, Bayesian image restoration, with two applications in spatial statistics, Ann. Inst. Stat. Math., 43, 1, 10.1007/BF00116466 Lee, 2018, Spatio-temporal areal unit modelling in R with conditional autoregressive priors using the CARBayesST package, J. Stat. Softw., 84, 1, 10.18637/jss.v084.i09 Martínez-Beneito, 2008, An autoregressive approach to spatio-temporal disease mapping, Stat. Med., 27, 2874, 10.1002/sim.3103 Li, 2012, Spatial modelling of lupus incidence over 40 years with changes in census areas, J. R. Stat. Soc. Ser. C. Appl. Stat., 61, 99, 10.1111/j.1467-9876.2011.01004.x Benjamin, 2018, Continuous inference for aggregated point process data, R. Stat. Soc., 181, 1125, 10.1111/rssa.12347 Johnson, 2019, A spatially discrete approximation to log-Gaussian Cox processes for modelling aggregated disease count data, Stat. Med., 38, 4871, 10.1002/sim.8339 Taylor, 2015, Bayesian inference and data augmentation schemes for spatial, spatiotemporal and multivariate log-Gaussian Cox processes in R, J. Stat. Softw., 63, 1, 10.18637/jss.v063.i07 Utazi, 2021, District-levelestimation of vaccination coverage: Discrete vs continuous spatial models, Stat. Med., 40, 2197, 10.1002/sim.8897 Paige, 2022, Design- and model-based approaches to small-area estimation in a low- and middle-income country context: Comparisons and recommendations, Surv. Stat. Methodol., 10, 50, 10.1093/jssam/smaa011 Wong, 2023 CSA, Central Statistical Authority, 2007 Population and Housing Census of Ethiopia. Country Level, Addis Ababa, Ethiopia, 2007. Gneiting, 2010, Continuous parameter spatio-temporal processes, 427 Giorgi, 2018, Geostatistical methods for disease mapping and visualization using data from spatio-temporally referenced prevalence surveys, Internat. Statist. Rev., 86, 571, 10.1111/insr.12268 Leroux, 2000, 179 Lee, 2011, A comparison of conditional autoregressive models used in Bayesian disease mapping, Spatial Spatio-Temp. Epidemiol., 2, 79, 10.1016/j.sste.2011.03.001 Rushworth, 2014, A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in greater London, Spatial Spatio-Temporal Epidemiol., 10, 29, 10.1016/j.sste.2014.05.001 Giorgi, 2017, PrevMap: An R package for prevalence mapping, J. Stat. Softw., 78, 1, 10.18637/jss.v078.i08 Johnson, 2018 EFDR, 2019 Waller, 2010, Disease mapping, 217, 10.1201/9781420072884-c14 Hoeting, 2006, Model selection for geostatistical models, Ecol. Appl., 16, 87, 10.1890/04-0576 Gelfand, 2010 Abeku, 2004, Effects of meteorological factors on epidemic malaria in Ethiopia: A statistical modelling approach based on theoretical reasoning, Parasitology, 128, 585, 10.1017/S0031182004005013 Teklehaimanot, 2004, Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia I. Patterns of lagged weather effects reflect biological mechanisms, Malar. J., 3 Giorgi, 2021, Model building and assessment of the impact of covariates for disease prevalence mapping in low-resource settings: To explain and to predict, J. R. Soc. Interface, 18, 10.1098/rsif.2021.0104 Bhatt, 2017, Improved prediction accuracy for disease risk mapping using Gaussian process stacked generalization, J. R. Soc. Interface, 14 McMahon, 2021, Remote sensing of environmental risk factors for malaria in different geographic contexts, Int. J. Health Geogr., 20, 1, 10.1186/s12942-021-00282-0 Yu, 2015, Projecting future transmission of malaria under climate change scenarios: Challenges and research needs, Crit. Rev. Environ. Sci. Technol., 45, 777, 10.1080/10643389.2013.852392