Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar

• DOI: 10.1016/j.epidem.2021.100534
• Publication Date: 2021-12-03T18:11:42Z
• Authors: Tanjona Ramiadantsoa; C. Jessica E. Met...; Antso Hasina Rahe...; Santatra Randrian...; Benjamin L. Rice; Amy Wesolowski; Fidiniaina Mamy R...; Fidisoa Rasambain...
• Keywords: Mobile phone; Metapopulation; Leverage (statistics); Pandemic; Geographical distance

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models disease spread to inform public health planning. However, in many LMICs, traditional data sets on commuting surveys well non-traditional sources mobile phone are lacking, or, where available, have only rarely been leveraged by community. Evaluating accuracy available measure transmission-relevant may be further hampered limited reporting suspected and laboratory confirmed infections. Here, we leverage case collected part dashboard collated via daily reports from Malagasy authorities reported cases SARS-CoV-2 across 22 regions Madagascar. We compare order timing when were with predictions metapopulation model Madagascar informed using various measures connectivity including gravity based different distance, Internal Migration Flow data, data. Overall, gravity-based Euclidean distance best predicted observed spread. The ranks most remote capital more difficult predict but interestingly, was differed those accurate. This suggests that there additional features mobility or consistently underestimated all approaches epidemiologically relevant. work highlights importance availability strengthening collaboration among institutions access critical - good they use, so building towards effective data-sharing pipelines essential.