A brief review and guidance on the spatiotemporal sampling designs for disease vector surveillance

TL;DR

This paper reviews spatiotemporal sampling methods for disease vector surveillance to help researchers collect representative data on mosquitoes and other vectors.

Contribution

The paper provides concise guidance on choosing optimal spatiotemporal sampling designs for vector-borne disease surveillance.

Findings

Non-probabilistic preferential sampling can lead to biased mosquito parameter estimates.

A mixed random and grid survey is optimal when little prior information is available.

Adaptive designs improve efficiency when previous data is available.

Abstract

Obtaining a representative sample of disease vectors (mosquitoes, flies, ticks, etc.) is essential for researchers to draw meaningful conclusions about the entire vector population in a target study area and during a specific study period. To achieve this, a carefully chosen surveillance design is required to ensure that the sample captures essential spatial and temporal variations in the target vector population(s) and/or that the study results can be generalized to the entire population. Designed-based and model-based spatiotemporal sampling (or in our context surveillance) designs can be used to maximize information gain within given resource constraints. In this paper, we aim to offer a concise overview of common spatiotemporal field sampling designs, their advantages and disadvantages and their practical applications in the context of surveillance and management of vector-borne diseases. At the end of the article, we offer guidance to help vector-borne disease surveillance planners design effective spatiotemporal surveillance interventions.

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•An overview of the main approaches and designs for spatio-temporal surveillance is provided.•Non-probabilistic preferential sampling can result in biased estimations of the mosquito parameters of interest.•When little information is available, a mixed random and grid survey is an optimal solution.•When previous information is available, adaptive designs can provide better gains towards a target.

An overview of the main approaches and designs for spatio-temporal surveillance is provided.

Non-probabilistic preferential sampling can result in biased estimations of the mosquito parameters of interest.

When little information is available, a mixed random and grid survey is an optimal solution.

When previous information is available, adaptive designs can provide better gains towards a target.

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