# 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.

## Key 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.