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Related Concept Videos

Malaria01:29

Malaria

Malaria pathogenesis in humans reflects a delicate interplay between parasite biology and host response. Clinical illness reflects a host’s immune response to the parasite’s asexual replication cycle, which is often asymptomatic in individuals with partial immunity. From the parasite's perspective, transmission between mosquito and human with minimal host pathology is evolutionarily advantageous. Among the six Plasmodium species infecting humans, P. falciparum and P. vivax dominate in global...

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Related Experiment Video

Updated: May 31, 2026

An In Vitro Model for Measuring Immune Responses to Malaria in the Context of HIV Co-infection
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Published on: October 6, 2015

Optimizing age-structured sampling for estimating the seroconversion rate in malaria seroepidemiology: a simulation

Yura K Ko1,2, Shilei Li3, Tom Britton4

  • 1Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden. yongra.ko@ki.se.

Scientific Reports
|May 29, 2026
PubMed
Summary
This summary is machine-generated.

Optimizing age-based sampling improves malaria seroconversion rate (SCR) estimation. Sampling strategies depend on transmission stability, seroreversion rate (SRR) knowledge, and transmission changes for precise malaria burden assessment.

Keywords:
AllocationMalariaPrecisionReverse catalytic modelSeroconversion rateSeroprevalence

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Area of Science:

  • Malaria epidemiology
  • Mathematical modeling
  • Biostatistics

Background:

  • Seroprevalence and seroconversion rate (SCR) are crucial for assessing malaria burden, especially in low-transmission areas.
  • Optimizing age-based sampling strategies can enhance the efficiency and precision of SCR estimation.
  • Systematic exploration of age-based sampling for malaria seroepidemiology is lacking.

Purpose of the Study:

  • To identify optimal age-based sampling strategies for malaria seroconversion rate (SCR) estimation.
  • To evaluate the impact of varying SCR, seroreversion rate (SRR), and SRR knowledge on sampling strategy effectiveness.
  • To assess sampling strategies under stable and changing malaria transmission scenarios.

Main Methods:

  • Utilized Monte Carlo simulations to explore various age-based sampling strategies.
  • Employed the reverse catalytic model and its extension to analyze malaria transmission dynamics.
  • Simulated scenarios with stable SCR, SCR reduction at a change point, and known/unknown SRR, using realistic parameter ranges for Plasmodium falciparum MSP1 responses.

Main Results:

  • In stable transmission, sampling older individuals improved precision in low-transmission settings, while younger individuals were more informative in high-transmission settings when SRR was known.
  • When SRR was unknown, sampling younger individuals and maintaining a balanced age distribution increased precision.
  • For changing transmission, sampling post-change born individuals improved post-change SCR estimation; balanced sampling was optimal when SRR was unknown.
  • Application to Sri Lankan data showed that an adult-skewed sample reduced precision and power for detecting transmission changes.

Conclusions:

  • Age-structured sampling significantly impacts the precision and power of malaria SCR estimation.
  • Optimal sampling strategies are context-dependent, varying with transmission intensity, SRR dynamics, and knowledge of SRR.
  • Thoughtful consideration of age-structured sampling is essential for efficient and accurate malaria burden assessment, especially in resource-limited settings.