A web-based application on contact tracing questionnaire

Funder: This project is currently seeking funding

Principal Investigators: Nhat Le, Ronald Geskus, Marc Choisy

Location of activity: Hanoi and Ho Chi Minh City, Viet Nam

Collaborator(s): Dr Pham Quang Thai, Epidemiology Department, National Institute of Hygiene and Epidemiology (NIHE), Vera Arntzen (Leiden University)

Purpose:

This study aims to develop a standardised format for the questionnaire on contacts and build a smart device app to collect contact-tracing information.

Importance:

The world becomes increasingly more vulnerable to pandemics of novel infectious agents. When a novel infection emerges, an efficient methodology to contain the spread is contact tracing, which aims to identify all contacts of a diagnosed case and test them for infection.

Contact tracing is generally performed in a rush and in a way that is not always carefully considered. Furthermore, the data are collected to address immediate public health questions and are rarely collected in a standard format.

We propose a system to collect contact tracing information in a safe and standardised way. Such a system fulfils immediate public health purposes like containing the outbreak and is also helpful for research purposes. For example, contact tracing data can provide information for estimating key epidemiological quantities such as the distribution of latency and incubation period. Precise and unbiased estimates of these quantities will improve the predictions from epidemiological and mathematical models and thus are extremely valuable for efficient and timely control of the disease.

Primary Objectives:

  • We design an electronic questionnaire on individual contact-tracing information, which is embedded into an app. This app connects to a central database in the cloud server. The app can also detect frequent errors during data entry, such as multiple formats of dates or Vietnamese free text. We will investigate how best to structure the questionnaires.
  • We write an R package that can read the raw contact data per individual into R and transform the data into a format that consists of possible sources of infection and the period of contact with each of them. The package also includes functionalities that appeared as a shiny app that visualises the transmission chain developed by Vera Arntzen.