Microscopic parasites intertwining with a globe

Are We Missing the Full Picture? How Sample Size Affects Schistosomiasis Research

"Unveiling the Hidden Complexities of Parasite Population Studies and What It Means for Public Health."


In epidemiological studies, it's ideal to examine every individual in a population to get answers; however, examining the whole population isn't practical for larger studies. Instead, researchers analyze a representative portion, known as a sample. A sample, however, may be biased and not representative of the actual population. One of the greatest dangers with a sample is if too small, as it may lack the power to detect differences between groups.

For population genetics, no single sample size will serve to answer all questions for all populations, since there can be differences in frequency and distribution of variation, the resolution and accuracy desired, in the amount of uncertainty in the estimates and basic biology among populations and species. Schistosomiasis, a parasitic disease, adds another layer of complexity to sample size determination.

A recent study by Barbosa et al. (2018) in the International Journal for Parasitology investigates the effect of sample size on estimates of genetic differentiation and effective population size for Schistosoma mansoni populations in Brazil. By analyzing parasite allele frequencies in two communities, the researchers shed light on the importance of extensive sampling for accurate insights.

Decoding Schistosoma Mansoni: Why Sample Size Matters

Microscopic parasites intertwining with a globe

Eradication or local extinction of the human parasite Schistosoma mansoni is a goal for many control programs. Population genetic analyses are helping to evaluate and guide these efforts; yet, what to sample, how to sample, and how densely to sample is not well established. The core of this study revolves around determining the S. mansoni allele frequency profile in nearly all infected inhabitants in two small Brazilian communities.

Researchers created subsamples representing 5-50% of all detected human infections, also known as infrapopulations. These samples were selected at random with replacement, and each size class was replicated 100 times to ensure statistical rigor. The mean pairwise differentiation for all infrapopulations (Di) and the variance effective population size (Ne) were calculated for each sample.

  • Genetic Differentiation (Di): Measures how genetically different parasite populations are from each other.
  • Effective Population Size (Ne): Indicates the number of breeding individuals in a population, which is vital for understanding its long-term viability.
Prior to community-wide treatment, the true mean Di was moderate (0.095-0.123) and Ne large (>30,000). Most samples of <50% of those infected produced estimates outside of 5% of the true value. The researchers determined extensive sampling is required for accurate estimates of these important population parameters. Characteristics such as population census size, infection prevalence, the community's treatment history and the degree of infrapopulation differentiation should be taken into account.

The Bigger Picture: Implications for Disease Control

This study underscores the critical need for extensive sampling in schistosomiasis research. As population structures change due to interventions like treatment programs, sampling requirements also shift, highlighting the importance of adapting strategies to maintain accuracy. Accurately measuring parasite differentiation and diversity is essential for informing effective public health strategies.

While the logistics of working with parasites that aren't Hardy-Weinberg populations make sampling complex, the genotypes are acquired somewhat at random from the environment, simplifying sampling. According to the authors, the most heavily infected individual gives the most accurate approximation of the population and the sampling doesn't have to be overly complex, but it does have to be extensive, otherwise, a large degree of error may be present.

Ultimately, by recognizing the impact of sample size, researchers and public health officials can refine their approaches, leading to more precise evaluations and more effective control programs, bringing us closer to eradicating diseases like schistosomiasis.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1016/j.ijpara.2018.10.001, Alternate LINK

Title: The Effect Of Sample Size On Estimates Of Genetic Differentiation And Effective Population Size For Schistosoma Mansoni Populations

Subject: Infectious Diseases

Journal: International Journal for Parasitology

Publisher: Elsevier BV

Authors: Lúcio M. Barbosa, Bruna C. Barros, Moreno De Souza Rodrigues, Luciano K. Silva, Mitermayer G. Reis, Ronald E. Blanton

Published: 2018-12-01

Everything You Need To Know

1

Why is a sample used in schistosomiasis research, and what are the potential limitations?

In schistosomiasis research, a sample is a representative portion of a population analyzed to understand the characteristics of the entire group. Due to the impracticality of examining every individual, especially in larger studies, researchers use samples to infer insights about the broader population. However, it's crucial to recognize that a sample may introduce bias and may not accurately reflect the true population parameters. The size of the sample can significantly impact the reliability of the findings.

2

What are Genetic Differentiation (Di) and Effective Population Size (Ne), and why are they important in the context of schistosomiasis research?

Genetic differentiation (Di) measures how genetically different parasite populations are from each other. Effective population size (Ne) indicates the number of breeding individuals in a population, which is vital for understanding its long-term viability. Both are key population parameters; in the study by Barbosa et al. (2018), accurate estimation of Di and Ne required extensive sampling.

3

According to the research, what happens when sample sizes are too small in Schistosoma mansoni population studies?

The Barbosa et al. (2018) study demonstrated that with samples representing less than 50% of infected individuals, the estimates often deviated more than 5% from the true value for parameters like genetic differentiation (Di) and effective population size (Ne). This indicates that smaller samples may lead to inaccurate conclusions about the parasite populations.

4

What are the broader implications of the Barbosa et al. (2018) findings for disease control and public health strategies related to schistosomiasis?

The implications of the Barbosa et al. (2018) findings are significant for disease control programs targeting Schistosoma mansoni. Inaccurate estimates of parasite population parameters, like genetic differentiation (Di) and effective population size (Ne), could lead to ineffective or misguided public health strategies. Therefore, extensive sampling, tailored to the specific characteristics of the population, is essential for informing effective interventions.

5

Besides sample size, what other factors should researchers consider when studying Schistosoma mansoni populations to ensure accurate and meaningful results?

Factors such as population census size, infection prevalence, a community's treatment history, and the degree of infrapopulation differentiation are crucial in determining appropriate sample sizes for schistosomiasis research. These factors influence the accuracy of estimates for parameters like genetic differentiation (Di) and effective population size (Ne), directly impacting the reliability of research findings and the effectiveness of control programs.

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