scieee AI-readable full text Open interactive document viewer

Survey on data availability and data needs for modelers during the COVID-19 pandemic

Mazzoli, Mattia; Varela-Lasheras, Irma; Namorado, Sónia; Caetano, Constantino; Leite, Andreia; Hermans, Lisa; Hens, Niel; Turkmen, Polen; Kalimeri, Kyriaki; Ferres, Leo; Cattuto, Ciro; Paolotti, Daniela; Verhulst, Stefaan

Abstract

As part of a study aimed to identify and review data needs and availability during the COVID-19 pandemic, including both traditional and non-traditional data sources, we created survey for the modeling community in Europe. In particular the survey aims to better understand the types of data used for modeling during the pandemic, their purpose, and their limitations as well as the unmet data needs of the modeling community.

Full text

25.07.2025 15:37 projectredcap.org Confidential Page 1 Survey on data availability and data needs for modelers during the COVID-19 pandemic The ESCAPE project aims to improve the efficiency and scalability of early pandemic response plans. Its research objectives are clustered in four topics: data readiness, analytics & tools, determinants of success, and decision aid blueprint. Within the data readiness topic, we aim to identify and review data needs and availability during the COVID-19 pandemic, including both traditional and non-traditional data sources. To guide this review, we have prepared a short survey for the modeling community, in order to: Better understand the types of data used for modeling during the pandemic, their purpose, and their limitations.Better understand the unmet data needs of the modeling community.Instructions: The survey is anonymous and consists of 7 questions. Most of them allow more than one answer. Questions 1 and 6 are followed by a series of sub-questions for each of the data types you select. We recommend that you complete the survey on a computer or tablet for formatting compatibility.  Thank you very much for your participation! 1. What are the main types of data you or your team used during the COVID-19 pandemic? Traditional PCR tests Serological data/antigen tests Viral load data (quantitative or semi-quantitative data) ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Please, specify: __________________________________________ Non-Traditional (1) (1) Includes data types not Mobility data collected with epidemiological purposes and/or Contact data relatively new data types. Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Please, specify: __________________________________________ 1.1. How did you access the data? Publicly available Agreement with governmental institutions Agreement with academic institutions Agreement with private sector I/we collected/had direct access to the data Others 25.07.2025 15:37 projectredcap.org Confidential Page 2 PCR tests Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Please, specify: __________________________________________ 1.2. In practical terms, which problems did you find accessing the data? Finding the right data and, if applicable, data owners Issues/delays around ethics approval to use the data Complicated protocols for data transfer Complicated protocols for data management once transferred PCR tests Serological data/antigen tests Viral load data ILI or other symptom related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data 25.07.2025 15:37 projectredcap.org Confidential Page 3 Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Data owners reluctant/unwi lling to share for privacy reasons Data owners reluctant/unwi lling to share for national security reasons Data owners reluctant/unwi lling to share for academic competition reasons Data owners reluctant/unwi lling to share for commercial reasons Others None PCR tests Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditonal) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data 25.07.2025 15:37 projectredcap.org Confidential Page 4 Others (non-traditional) Please, specify: __________________________________________ 1.3. For your specific purposes, could the data have had higher quality in terms of: Data preparation and processing Machine-read ability Spatial granularity Temporal granularity Temporal availability Demographica l or medical granularity PCR test Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Comparability with other data sets Linkage to other data sets Biases Privacy Others None PCR test Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data 25.07.2025 15:37 projectredcap.org Confidential Page 5 Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Please, specify: __________________________________________ 2. What type of analysis and/or modeling strategies Mathematical/mechanistic models have you used? Statistical/phenomenological models Machine learning models Others Please, specify: __________________________________________ 3. Under which of these general questions(2) does your Is an outbreak occurring and is it caused by a research fall? (2) General policy questions based on novel pathogen or a new variant? Bhatia et al. 2023. How virulent is the pathogen? How quickly is the pathogen spreading? How does the epidemic look like in the near future given certain assumptions? How do we monitor its impact, in health and/or socio-economic terms? How do we respond to control the epidemic (e.g. intervention assessment, including vaccination)? Others Please, specify: __________________________________________ 4. To your knowledge, were the results of these Yes analyses directly used to inform public health No policies? I don't know How? __________________________________________ 25.07.2025 15:37 projectredcap.org Confidential Page 6 Why? __________________________________________ 5. If you combined 2 or more of this data types in PCR tests your research, please indicate which ones: Serological data/antigen tests Viral load data (quantitative or semi-quantitative data) ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Please, specify: __________________________________________ Please, specify: __________________________________________ 6. What other data types did you need, or would you We had access to all the data we needed have liked to use, in your research? PCR tests Serological data/antigen tests Viral load data (quantitative or semi-quantitative data) ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Please, specify: __________________________________________ 25.07.2025 15:37 projectredcap.org Confidential Page 7 Please, specify: __________________________________________ 6.1. Why did not you use them? Not available at all Not available in effective time Data preparation and processing PCR tests Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Machine-readabil ity Spatial granularity Temporal granularity Temporal availability Demographical or clinical granularity PCR test Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data 25.07.2025 15:37 projectredcap.org Confidential Page 8 Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Comparability with other data sets Linkage to other data sets Biases Privacy Others PCR test Serological data/antigen tests Viral load data ILI or other symptom-related data Hospitalizations ICU admission data Deaths Genomic data Vaccination related data Data from epidemiological cohort studies Others (traditional) Mobility data Contact data Electronic health record data Wastewater data Crowdsourced /participatory data Social media data Socio-economic or demographic data Contact-tracing data Others (non-traditional) Please, specify: __________________________________________ 6.2. Why/for what purpose would it have been important to have this data? __________________________________________ 25.07.2025 15:37 projectredcap.org Confidential Page 9 7. Other comments regarding data needs, accessibility, readiness, etc. __________________________________________