Malaria transmission modelling and conditional prevention allocation in Uganda

Abstract

Malaria transmission models can generate precise intervention rankings even when their parameters, observation mappings and programme costs remain uncertain. I evaluated an age-stratified SEIR-SEI framework in a standardised population of one million, using an unchanged 36-month historical synthetic target. The reconciled implementation maintained virtual age-group totals, fitted the transmission composite K = {beta}M, integrated infectious onsets and disease deaths, and compared interventions from one phase-aligned baseline state over 720 days. An aggregate vaccine effect entered child infection before simulation, allowing transmission feedback.

Five calibration seeds gave total-series R{superscript 2} 0.9537; subgroup fits were weaker. The closed-form unforced reproduction index, 6.3787, matched the six-state next-generation matrix. The baseline produced 528,041 expected reported episodes. ITN coverage of 50% averted 36,692 episodes; vaccine coverage of 70% averted 2,123 under the assumed aggregate mechanism. At a hypothetical US$2 million additional prevention budget, five allocation seeds and a 10,201-point boundary grid selected 71.43% ITN coverage, averting 52,482.83 reported episodes. The same corner won within a 115-portfolio pool for all 300 assumed parameter draws and remained selected after 40 repeated noisy-target recalibrations. Halving the IRS round price and using two rounds changed the selected mix to 40.07% ITN and 21.95% IRS. All 17 mathematical and numerical assertions passed.

The study demonstrates reproducible conditional calculations and identifies important structural confounding. It does not establish empirical Uganda programme effectiveness, a clinical treatment allocation or a national cost-effectiveness recommendation. Empirical use requires compatible surveillance observations, a cohort-based vaccine mechanism, treatment-specific clinical effects and locally measured programme resources.

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BibTeX RIS

BibTeX

@misc{patel2026malaria,
  title = {{Malaria transmission modelling and conditional prevention allocation in Uganda}},
  author = {J. H. Patel and J. Mulangwa and M. Musaba},
  howpublished = {medRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.23.26365767},
  url = {https://www.medrxiv.org/content/10.64898/2026.10.23.26365767v1},
  note = {CC BY},
}

RIS

TY  - UNPB
TI  - Malaria transmission modelling and conditional prevention allocation in Uganda
AU  - J. H. Patel
AU  - J. Mulangwa
AU  - M. Musaba
PY  - 2026
DA  - 2026/10/23
PB  - medRxiv
DO  - 10.64898/2026.10.23.26365767
UR  - https://www.medrxiv.org/content/10.64898/2026.10.23.26365767v1
AB  - Malaria transmission models can generate precise intervention rankings even when their parameters, observation mappings and programme costs remain uncertain. I evaluated an age-stratified SEIR-SEI framework in a standardised population of one million, using an unchanged 36-month historical synthetic target. The reconciled implementation maintained virtual age-group totals, fitted the transmission composite K = {beta}M, integrated infectious onsets and disease deaths, and compared interventions from one phase-aligned baseline state over 720 days. An aggregate vaccine effect entered child infection before simulation, allowing transmission feedback.  Five calibration seeds gave total-series R{superscript 2} 0.9537; subgroup fits were weaker. The closed-form unforced reproduction index, 6.3787, matched the six-state next-generation matrix. The baseline produced 528,041 expected reported episodes. ITN coverage of 50% averted 36,692 episodes; vaccine coverage of 70% averted 2,123 under the assumed aggregate mechanism. At a hypothetical US$2 million additional prevention budget, five allocation seeds and a 10,201-point boundary grid selected 71.43% ITN coverage, averting 52,482.83 reported episodes. The same corner won within a 115-portfolio pool for all 300 assumed parameter draws and remained selected after 40 repeated noisy-target recalibrations. Halving the IRS round price and using two rounds changed the selected mix to 40.07% ITN and 21.95% IRS. All 17 mathematical and numerical assertions passed.  The study demonstrates reproducible conditional calculations and identifies important structural confounding. It does not establish empirical Uganda programme effectiveness, a clinical treatment allocation or a national cost-effectiveness recommendation. Empirical use requires compatible surveillance observations, a cohort-based vaccine mechanism, treatment-specific clinical effects and locally measured programme resources.
ER  -

Abstract

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