Spatial disparities in impoverishing effects of out-of-pocket health payments in Malawi

References

• World Health Organization (WHO). The world health report: health systems financing. Geneva: World Health Organization; 2010.
   Google Scholar
• Xu K, Evans DB, Kawabata K, et al. Household catastrophic health expenditures: a multi-country analysis. Lancet. 2003;362:565–12.
   Web of Science ®Google Scholar
• Wagstaff A, Van Doorslaer E. Catastrophe and impoverishment in paying for health care: with applications to Vietnam 1993–1998. Health Econ. 2003;934:921–934.
   Web of Science ®Google Scholar
• World Health Organization and International Bank for Reconstruction and Development/The World Bank. Global monitoring report on financial protection in health 2019. Geneva; 2020. Licence: CC BY-NC-SA 3.0 IGO, editor.
   Google Scholar
• Wagstaff A, Flores G, Smitz M, et al. Progress on impoverishing health spending in 122 countries: a retrospective observational study. Lancet. 2018;6:5–10.
   Web of Science ®Google Scholar
• Van Doorslaer E, Donnell OO. Effect of payments for health care on poverty estimates in 11 countries in Asia: an analysis of household survey data eff ect of payments for health care on poverty estimates in 11 countries in Asia: an analysis of household survey data. Lancet. 2006;368:1357–1364.
   PubMed Web of Science ®Google Scholar
• WHO. WHO African region expenditure atlas. Brazzaville: Regional Office for Africa; 2014.
   Google Scholar
• Xu K, Saksena P, Jowett M, et al. Exploring the thresholds of health expenditure for protection against financial risk. Geneva (Switzerland); 2010. Report No.: 9.
   Google Scholar
• Government of the Republic of Malawi. Health sector strategic plan II 2017–2022. Toward universal health covarage. Lilongwe (Malawi): Ministry of Health(MoH), Government of Malawi; 2017.
   Google Scholar
• World Bank Health Nutrition and Population Team Malawi. Spending for health in Malawi: current trends and strategies to improve efficiency and equity in health financing. 2021.
   Google Scholar
• Borghi J, Munthali S, Million LB, et al. Health financing at district level in Malawi: an analysis of the distribution of funds at two points in time. Health Policy Plann. 2017;33:59–69.
   Web of Science ®Google Scholar
• Ministry of Health M. Malawi national health accounts a summary brief of Fiscal years 2015/16, 2016/17, and 2017/18. Lilongwe (Malawi): Ministry of Health(MoH), Government of Malawi; 2020.
   Google Scholar
• The World Bank. Fiscal space for health in Malawi and revenue potential of ‘innovative financing’. Lilongwe (Malawi): World Bank Group; 2015.
   Google Scholar
• Abiiro GA, Mbera GB, De Allegri M. Gaps in universal health coverage in Malawi: a qualitative study in rural communities. BMC Health Serv Res. 2014;14:1–10.
   PubMed Web of Science ®Google Scholar
• Chansa C, Pattnaik A. Expanding health care provision in a low-income country: the experience of Malawi. Washington (DC); 2018. Universal Health Coverage Study Series No. 34.
   Google Scholar
• Manthalu G, Yi D, Farrar S, et al. The effect of user fee exemption on the utilization of maternal health care at mission health facilities in Malawi. Health Policy Plann. 2016;31:1184–1192.
   PubMed Web of Science ®Google Scholar
• Chirwa ML, Kazanga I, Faedo G, et al. Promoting universal financial protection: contracting faith-based health facilities to expand access - lessons learned from Malawi. Health Res Policy Syst. 2013;11:1–9.
   PubMed Web of Science ®Google Scholar
• Mchenga M, Chirwa GC, Chiwaula LS. Impoverishing effects of catastrophic health expenditures in Malawi. Int J Equity Health. 2017;16:1–8.
   PubMed Web of Science ®Google Scholar
• Kazembe LN, Namangale JJ. A Bayesian multinomial model to analyse spatial patterns of childhood co-morbidity in Malawi. Eur J Epidemiol. 2007;22:545–556.
   PubMed Web of Science ®Google Scholar
• Chirombo J, Lowe R, Kazembe L. using structured additive regression models to estimate risk factors of malaria: analysis of 2010 Malawi malaria indicator survey data. PLoS One. 2014;9:1–10.
   Web of Science ®Google Scholar
• Ngwira A, Kazembe LN. Bayesian random effects modelling with application to childhood anaemia in Malawi. BMC Public Health. 2015;15:1–11.
   PubMed Web of Science ®Google Scholar
• Kazembe LN, Kamndaya MS. Hierarchical spatial modelling of pneumonia prevalence when response outcome has misclassification error: applications to household data from Malawi. Spat Spatiotemporal Epidemiol. 2016;16:35–42.
   PubMedGoogle Scholar
• Nutor JJ, Duah HO, Agbadi P, et al. Spatial analysis of factors associated with HIV infection in Malawi: indicators for effective prevention. BMC Public Health. 2020;20:1–14.
   PubMed Web of Science ®Google Scholar
• Malawi IFPRI. IFPRI key facts series : poverty. Lilongwe (Malawi): IFPRI Malawi; 2019.
   Google Scholar
• Kazembe LN, Appleton CC, Kleinschmidt I. Choice of treatment for fever at household level in Malawi: examining spatial patterns. Malar J. 2007;6:1–13.
   PubMed Web of Science ®Google Scholar
• Malawi Governemnt. Closing the gap: why achieving universal health coverage in Malawi now requires targeted investment in underperforming and underserved districts public. 2020.
   Google Scholar
• Government of Malawi Ministry of Health and Population. Malawi Harmonised Health Facility Assessment (HHFA) 2018/2019 report. Government of Malawi; 2019.
   Google Scholar
• Akazili J, Ataguba JE, Kanmiki EW, et al. Assessing the impoverishment effects of out-of-pocket healthcare payments prior to the uptake of the national health insurance scheme in Ghana. BMC Int Health Hum Rights. 2017;17:1–8.
   PubMed Web of Science ®Google Scholar
• Obse AG, Ataguba JE. Assessing medical impoverishment and associated factors in health care in Ethiopia. BMC Int Health Hum Rights. 2020;20:1–9.
   PubMed Web of Science ®Google Scholar
• Shi W, Chongsuvivatwong V, Geater A, et al. Effect of household and village characteristics on financial catastrophe and impoverishment due to health care spending in Western and Central Rural China: a multilevel analysis. Health Res Policy Syst. 2011;16:1–10.
   Google Scholar
• Van Minh H, Xuan TB. Assessing the household financial burden associated with the chronic non-communicable diseases in a rural district of Vietnam. Global Health Action. 2012;18892(5): 1.
   Google Scholar
• Minh H, Van Thi N, Phuong K, et al. Financial burden of household out-of pocket health expenditure in Viet Nam: findings from the national living standard survey 2002–2010. Soc Sci Med. 2013;96:258–263.
   PubMed Web of Science ®Google Scholar
• Chaix B, Merlo J, Chauvin P. Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France. J Epidemiol Community Health. 2005;59:517–526.
   PubMed Web of Science ®Google Scholar
• Arcaya M, Brewster M, Zigler CM, et al. Area variations in health: a spatial multilevel modeling approach. Health Place. 2012;18:824–831.
   PubMed Web of Science ®Google Scholar
• The National Statistical Office of Malawi. Integrated household survey 2016–2017. Zomba (Malawi): Government of Malawi; 2017.
   Google Scholar
• O’Donnell O, Van Doorslaer E. Analyzing health equity using household survey data. A guide to techniques and their implementation. Washington (DC): World Bank Institute Learning Resouces Series; 2007. p. 1–220.
   Google Scholar
• The National Statistical Office of Malawi, The World Bank Poverty and Equity Global Practice. Methodology for poverty measurements in Malawi (2016/17). Zomba (Malawi): National Statistical Office; 2018.
   Google Scholar
• World Bank Group. Povert & equity brief sub-Saharan Africa Malawi. https://databank.worldbank.org/data/download/poverty/33EF03BB-9722-4AE2-ABC7-AA2972D68AFE/Global_POVEQ_MWI.pdf: World Bank Group; 2020.
   Google Scholar
• Mulaga AN, Kamndaya MS, Masangwi SJ. Examining the incidence of catastrophic health expenditures and its determinants using multilevel logistic regression in Malawi. PLoS One. 2021;16:1–17.
   Web of Science ®Google Scholar
• Goldstein H. Multilevel statistical models. 3rd ed. London: Arnold; 2003.
   Google Scholar
• Congdon P. Applied Bayesian modelling. 2nd ed. West Sussex: John Wiley & Sons, Ltd; 2014.
   Google Scholar
• Leroux BG, Lei X, Breslow N. Estimation of disease rates in small areas: a new mixed model for spatial dependence. Stat Model Epidemiol Environ Clin Trials. 1999;116:179–191.
   Google Scholar
• Ma J, Mitchell G, Dong G, et al. Inequality in Beijing : a spatial multilevel analysis of perceived environmental hazard and self-rated health inequality in Beijing. Ann Am Assoc Geogr. 2017;107:109–129.
   Web of Science ®Google Scholar
• MacNab YC. On Gaussian Markov random fields and Bayesian disease mapping. Stat Methods Med Res. 2011;20:49–68.
   PubMed Web of Science ®Google Scholar
• Ma J, Chen Y, Dong G. Flexible spatial multilevel modeling of neighborhood satisfaction in Beijing. Prof Geogr. 2018;70:10–21.
   Web of Science ®Google Scholar
• Congdon P. Representing spatial dependence and spatial discontinuity in ecological epidemiology: a scale mixture approach. Stochastic Environ Res Risk Assess. 2017;31:291–304.
   Web of Science ®Google Scholar
• Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J R Stat Soc Ser B (Stat Methodol). 2009;71:319–392.
   Web of Science ®Google Scholar
• Blangiardo M, Cameletti M, Baio G, et al. Spatial and spatio-temporal models with R-INLA. Spat Spatiotemporal Epidemiol. 2013;4:33–49.
   PubMedGoogle Scholar
• Spiegelhalter DJ, Best NG, Carlin BP, et al. Bayesian measures of model complexity and fit. J R Stat Soc Ser B (Stat Methodol). 2002;64:583–639.
   Google Scholar
• Ngcamphalala C, Ataguba JE. An assessment of financial catastrophe and impoverishment from out-of-pocket health care payments in Swaziland. Global Health Action. 2018;1428473(11):1.
   Google Scholar
• Government of the Republic of Malawi. The Malawi noncommunicable diseases & injuries poverty commission report. Lilongwe (Malawi): Malawi NCDI Poverty Commission; 2018.
   Google Scholar
• Nakovics MI, Brenner S, Bongololo G, et al. Determinants of healthcare seeking and out-of-pocket expenditures in a “free” healthcare system: evidence from rural Malawi. Health Econ Rev. 2020;10:1–12.
   PubMed Web of Science ®Google Scholar
• Wang Q, Brenner S, Kalmus O, et al. The economic burden of chronic non- communicable diseases in rural Malawi : an observational study. BMC Health Serv Res. 2016;16:1–9.
   PubMed Web of Science ®Google Scholar
• Mendis FK, Cameron A, Laing R Jr, et al. The availability and affordability of selected essential medicines for chronic diseases in six low- and middle-income countries. Bull World Heal Organ. 2007;84:279–288.
   Web of Science ®Google Scholar
• Mwandira RH. Examining equity in out-of-pocket expenditures and utilization of healthcare services in Malawi. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/pg15bj50p: Oregon State University; 2011.
   Google Scholar
• Hennessee I, Chinkhumba J, Hagen MB, et al. Household costs among patients hospitalized with malaria : evidence from a national survey in Malawi, 2012. Malar J. 2017:1–12. DOI:10.1186/s12936-016-1650-6
   PubMed Web of Science ®Google Scholar
• Shin H, Ngwira LG, Tucker A, et al. Patient-incurred cost of inpatient treatment for tuberculosis in rural Malawi. Trop Med Int Health. 2020;25:624–634.
   PubMed Web of Science ®Google Scholar
• Leive A, Xu K. Coping with out-of-pocket health payments: empirical evidence from 15 African countries. Bull World Health Organ. 2008;86:849–856.
   PubMed Web of Science ®Google Scholar