|
1 | 1 |
|
| 2 | +@misc{murray-watson_modelling_2025, |
| 3 | + title = {Modelling the long-term demographic and epidemiological trends in {Malawi}}, |
| 4 | + copyright = {http://creativecommons.org/licenses/by/4.0/}, |
| 5 | + url = {http://medrxiv.org/lookup/doi/10.1101/2025.09.25.25336670}, |
| 6 | + doi = {10.1101/2025.09.25.25336670}, |
| 7 | + abstract = {1 |
| 8 | + Abstract |
| 9 | + Malawi is facing a dual burden of disease, with an increase in non-communicable diseases coinciding with still-high infectious disease burdens. What this will look like in the future, and how it will impact demand for healthcare, is unknown. In this study, we use the Thanzi La Onse (TLO) model - an individual-based “all diseases – whole health-system” model calibrated to Malawi’s demographic, epidemiological, and healthcare data - to project population, disease burdens, and healthcare demand from 2020 to 2070. |
| 10 | + We project Malawi’s population to grow from 19.5 million in 2020 to 54.2 million in 2070, with median age rising from 17 to 25 years. Infectious disease burdens, particularly HIV/AIDS, TB, malaria, and acute respiratory infections, will decline, though cancers, cardiometabolic diseases, and mental health disorders burdens will increase and account for over one-third of disability-adjusted life years by 2070. Demand for healthcare grows across all cadres, with the steepest increases in clinical and mental health services. |
| 11 | + Our results highlight the epidemiological and demographic shifts projected to occur in Malawi. In particular, we show the shift away from infectious and disease of childhood toward NCDs and age-related conditions will require adaptations in Malawi’s health system.}, |
| 12 | + language = {en}, |
| 13 | + urldate = {2025-11-14}, |
| 14 | + publisher = {Public and Global Health}, |
| 15 | + author = {Murray-Watson, Rachel E. and Molaro, Margherita and Mangal, Tara D. and Mohan, Sakshi and She, Bingling and Bhatia, Sangeeta and Collins, Joseph H. and Janoušková, Eva and Colbourn, Tim and Phillips, Andrew N. and Hallett, Timothy B.}, |
| 16 | + month = sep, |
| 17 | + year = {2025}, |
| 18 | + keywords = {Analyses using the model}, |
| 19 | +} |
| 20 | + |
| 21 | +@misc{mohan_method_2025, |
| 22 | + title = {Method for costing a health system using a {Health} {Systems} {Model}}, |
| 23 | + copyright = {© 2025, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution 4.0 International), CC BY 4.0, as described at http://creativecommons.org/licenses/by/4.0/}, |
| 24 | + url = {https://www.medrxiv.org/content/10.1101/2025.01.22.25320881v1}, |
| 25 | + doi = {10.1101/2025.01.22.25320881}, |
| 26 | + abstract = {Objectives Modelling approaches that consider system-wide delivery platforms rather than single diseases are increasingly recognized as crucial for the economic evaluation of policy and investment choices and can be instrumental in forward-looking policy formulation. This paper develops a costing approach tailored to one such model, the Thanzi La Onse (TLO) model of Malawi’s healthcare system, to estimate healthcare delivery costs under varying health system assumptions. |
| 27 | +Methods We developed a mixed-method costing approach to estimate the total cost of healthcare delivery in Malawi using the TLO model, from a healthcare provider perspective. Through an iterative adjustment of key costing parameters, we attempted to align our model-based estimates with real-world expenditure and budget data. Costs were estimated over an 8-year period (2023–2030) under alternative scenarios of health system capacity, including supply chain performance and the size of the health workforce. |
| 28 | +Results A detailed comparison of our cost estimates against expenditure and budget data demonstrates the reliability of our costing method and assumptions, for the conditions and resources captured by the model. Under current health system capacity, the total cost of healthcare delivery in Malawi between 2023 and 2030 was estimated at \$1.53 billion [95\% confidence interval, \$1.51b -\$1.54b], which translates to an average annual cost of \$309.83 million [\$306.17m -\$313.56m]. The estimation of costs under alternative scenarios demonstrates the importance of capturing feedback effects to correctly forecast healthcare costs. |
| 29 | +Conclusion Mixed-method costing used within health system models, such as TLO, is a feasible and robust method for estimating healthcare delivery costs. This approach can provide valuable insights for health sector planning and resource allocation.}, |
| 30 | + language = {en}, |
| 31 | + urldate = {2025-11-06}, |
| 32 | + publisher = {medRxiv}, |
| 33 | + author = {Mohan, Sakshi and Mangal, Tara D. and Manthalu, Gerald and Mfutso-Bengo, Joseph and Molaro, Margherita and Nkhoma, Dominic and She, Bingling and Tafesse, Wiktoria and Twea, Pakwanja Desiree and Walker, Simon and Chalkley, Martin and Colbourn, Tim and Hallett, Timothy B. and Phillips, Andrew and Revill, Paul}, |
| 34 | + month = jan, |
| 35 | + year = {2025}, |
| 36 | + note = {Pages: 2025.01.22.25320881}, |
| 37 | + keywords = {overview of the model}, |
| 38 | +} |
| 39 | + |
| 40 | +@article{murray-watson_impact_2025, |
| 41 | + title = {The impact of precipitation on {ANC} service utilisation and healthcare access in {Malawi}}, |
| 42 | + volume = {15}, |
| 43 | + copyright = {2025 The Author(s)}, |
| 44 | + issn = {2045-2322}, |
| 45 | + url = {https://www.nature.com/articles/s41598-025-21645-8}, |
| 46 | + doi = {10.1038/s41598-025-21645-8}, |
| 47 | + abstract = {Malawi is vulnerable to climate-related shocks, which are projected to worsen. Whilst some dimensions of this vulnerability have been characterised, little is known about healthcare sector resilience. Coupling facility-specific data on antenatal care (ANC) service provision in Malawi with gridded precipitation data from 2012-2024 we use linear regression analyses to characterise the historic relationship between precipitation and healthcare access. We estimate that precipitation negatively impacted ANC service utilisation in Malawi, with up to 1 in 20 appointments disrupted annually in some districts. Projecting further to 2060 indicates that, cumulatively, up to 250,000 pregnancies could be affected. Notably, if precipitation patterns from 1941 to 1953 had persisted into the 21st century, disruptions between 2012 and 2024 would be a hundred times less frequent, highlighting the significant influence of anthropogenic climate change on healthcare access. In a country already facing high maternal and neonatal mortality, such disruptions could further hinder access to care and worsen health outcomes. To mitigate this, interventions should focus on preserving or improving the physical accessibility of facilities, particularly through resilient transport services and road networks.}, |
| 48 | + language = {en}, |
| 49 | + number = {1}, |
| 50 | + urldate = {2025-11-06}, |
| 51 | + journal = {Scientific Reports}, |
| 52 | + author = {Murray-Watson, Rachel E. and Molaro, Margherita and Murray-Watson, Rebecca J. and Mohan, Sakshi and She, Bingling and Mangal, Tara and Collins, Joseph H. and Bhatia, Sangeeta and Janoušková, Eva and Hallett, Timothy B.}, |
| 53 | + month = oct, |
| 54 | + year = {2025}, |
| 55 | + note = {Publisher: Nature Publishing Group}, |
| 56 | + keywords = {Other analyses}, |
| 57 | + pages = {37896}, |
| 58 | +} |
| 59 | + |
2 | 60 | @article{she_health_2025, |
3 | 61 | title = {Health impacts of expanding different health workforce cadres under a limited budget in {Malawi}}, |
4 | 62 | url = {https://www.medrxiv.org/content/early/2025/09/15/2025.09.13.25335695}, |
@@ -118,22 +176,6 @@ @misc{mangal_system-wide_2025 |
118 | 176 | keywords = {Analyses using the model}, |
119 | 177 | } |
120 | 178 |
|
121 | | -@article{murray-watson_extreme_2025, |
122 | | - title = {Extreme {Weather} and {Healthcare} {Access} in {Malawi}: {The} {Impact} of {Precipitation} on {ANC} {Service} {Utilisation}}, |
123 | | - copyright = {http://creativecommons.org/licenses/by/4.0/}, |
124 | | - shorttitle = {Extreme {Weather} and {Healthcare} {Access} in {Malawi}}, |
125 | | - url = {http://medrxiv.org/lookup/doi/10.1101/2025.04.15.25325855}, |
126 | | - doi = {10.1101/2025.04.15.25325855}, |
127 | | - abstract = {Malawi is vulnerable to climate-related shocks, which are projected to worsen. Whilst some dimensions of this vulnerability have been characterised, little is known about healthcare sector resilience. Coupling facility-specific data on antenatal care (ANC) service provision in Malawi with gridded precipitation data, we use regression analyses to characterise the historic relationship between precipitation and healthcare access. We estimate that, between 2012 and 2024, precipitation negatively impacted ANC service utilisation in Malawi, with up to 1 in 20 appointments disrupted annually in some districts. Projecting further to 2060 indicates that, cumulatively, up to 250,000 pregnancies could be affected. Notably, if precipitation patterns from 1941–1953 had persisted into the 21st century, disruptions between 2012 — 2024 would be a hundred times less frequent, highlighting the significant influence of anthropogenic climate change on healthcare access. In a country already facing high maternal and neonatal mortality, such disruptions could further hinder access to care and worsen health outcomes.}, |
128 | | - language = {en}, |
129 | | - urldate = {2025-05-19}, |
130 | | - journal = {MedrXiv}, |
131 | | - author = {Murray-Watson, Rachel E. and Molaro, Margherita and Murray-Watson, Rebecca J. and Mohan, Sakshi and She, Bingling and Mangal, Tara and Collins, Joseph H. and Bhatia, Sangeeta and Janoušková, Eva and Hallett, Timothy B.}, |
132 | | - month = apr, |
133 | | - year = {2025}, |
134 | | - keywords = {Analyses using the model}, |
135 | | -} |
136 | | - |
137 | 179 | @article{mangal_modelling_2025, |
138 | 180 | title = {Modelling health outcomes of a decade of {HIV}, malaria and tuberculosis initiatives, {Malawi}}, |
139 | 181 | volume = {103}, |
|
0 commit comments