Biological Sciences Division
Published October 28, 2025 | Version v1
Journal article Metadata-only

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions

Creators

  • 1. University of Melbourne
  • 2. University of Chicago
  • 3. University of Ghana
  • 4. Ghana Health Service
  • 5. New York University

Description

Here, we introduce a new endpoint 'census population size' to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (MOIvar), based on the hyper-diversity of the var multigene family. We present a Bayesian approach to estimate MOIvar from sequencing and counting the number of unique DBLα tags (or DBLα types) of var genes, and derive from it census population size by summation of MOIvar in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high, seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by >90% and decreased parasite prevalence by ~40–50%, significant reductions in var diversity, MOIvar, and population size were observed in ~2000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short-lived and 32 months after IRS was discontinued and SMC was introduced, var diversity and population size rebounded in all age groups except for the younger children (1–5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the var population genetic characteristics of a high-transmission system (high var diversity; low var repertoire similarity), demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Data availability

The sequences utilized in this study are publicly available in GenBank under BioProject Number: PRJNA 396962. All data associated with this study, including de-identified individual participant data, are available in the manuscript, appendices, and on GitHub at https://github.com/UniMelb-Day-Lab/Census_Pop_Size_Pf_Ghana. Redistribution or reuse of these data requires proper attribution and prior approval. Researchers interested in further use of these data should contact the Malaria Reservoir Study Team, represented by the corresponding author, Prof. Karen Day (karen.day@unimelb.edu.au), to discuss how these data will be utilized for academic or research purposes and, if appropriate, to identify opportunities for collaboration. The PCR protocol and primer sequences are described in Appendix 1 and available on GitHub (https://github.com/UniMelb-Day-Lab/Pfalciparum_varDBLalpha_PCR; Tiedje, 2025). All custom code is available in an open source GitHub repository: (1) DBL Cleaner pipeline is available at https://github.com/UniMelb-Day-Lab/DBLaCleaner (Tan and Tiedje, 2023); (2) clusterDBLalpha pipeline is available at https://github.com/Unimelb-Day-Lab/clusterDBLalpha (Tonkin-Hill and Tiedje, 2017); and the (3) classifyDBLalpha pipeline is available at https://github.com/Unimelb-Day-Lab/classifyDBLalpha (Tonkin-Hill and Pesántez, 2019). A dataset and tutorial to demo this custom code is available at https://github.com/UniMelb-Day-Lab/tutorialDBLalpha (Tiedje and Tan, 2025). For additional information on the use of the Bayesian approach to estimate MOIvar please see https://github.com/qzhan321/Bayesian-formulation-varcoding-MOI-estimation(Zhan, 2024).

The following data sets were generated:

Malaria Reservoir Study Team (2017) NCBI BioSample ID SAMN41081346. Bongo District Ghana Study (GHSurvey7). https://www.ncbi.nlm.nih.gov/biosample/SAMN41081346

Tiedje KE Zhan Q (2025) GitHub ID Census_Pop_Size_Pf_Ghana. Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions. https://github.com/UniMelb-Day-Lab/Census_Pop_Size_Pf_Ghana

The following previously published data sets were used:

Malaria Reservoir Study Team (2016) NCBI BioSample ID SAMN11606536. Bongo District Ghana Study (GHPilot-GHSurvey6). https://www.ncbi.nlm.nih.gov/biosample/SAMN11606536

Additional details

Identifiers

DOI
10.7554/elife.91411.4
Other
oai:uchicago.tind.io:16538

Funding

Fogarty International Center
R01-TW009670
National Institute of Allergy and Infectious Diseases
R01-AI149779

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Ecology and Evolution, Genetics, Genomics, and Systems Biology