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Community vulnerability and mobility: What matters most in spatio-temporal modeling of the COVID-19 pandemic?

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  • Carroll, Rachel
  • Prentice, Christopher R.

Abstract

Community vulnerability is widely viewed as an important aspect to consider when modeling disease. Although COVID-19 does disproportionately impact vulnerable populations, human behavior as measured by community mobility is equally influential in understanding disease spread. In this research, we seek to understand which of four composite measures perform best in explaining disease spread and mortality, and we explore the extent to which mobility account for variance in the outcomes of interest. We compare two community mobility measures, three composite measures of community vulnerability, and one composite measure that combines vulnerability and human behavior to assess their relative feasibility in modeling the US COVID-19 pandemic. Extensions – via temporally dependent fixed effect coefficients – of the commonly used Bayesian spatio-temporal Poisson disease mapping models are implemented and compared in terms of goodness of fit as well as estimate precision and viability. A comparison of goodness of fit measures nearly unanimously suggests the human behavior-based models are superior. The duration at residence mobility measure indicates two unique and seemingly inverse relationships between mobility and the COVID-19 pandemic: the findings indicate decreased COVID-19 presence with decreased mobility early in the pandemic and increased COVID-19 presence with decreased mobility later in the pandemic. The early indication is likely influenced by a large presence of state-issued stay at home orders and self-quarantine, while the later indication likely emerges as a consequence of holiday gatherings in a country under limited restrictions. This study implements innovative statistical methods and furnishes results that challenge the generally accepted notion that vulnerability and deprivation are key to understanding disparities in health outcomes. We show that human behavior is equally, if not more important to understanding disease spread. We encourage researchers to build upon the work we start here and continue to explore how other behaviors influence the spread of COVID-19.

Suggested Citation

  • Carroll, Rachel & Prentice, Christopher R., 2021. "Community vulnerability and mobility: What matters most in spatio-temporal modeling of the COVID-19 pandemic?," Social Science & Medicine, Elsevier, vol. 287(C).
    • Handle: RePEc:eee:socmed:v:287:y:2021:i:c:s0277953621007279
    DOI: 10.1016/j.socscimed.2021.114395
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    1. Pierre Nouvellet & Sangeeta Bhatia & Anne Cori & Kylie E. C. Ainslie & Marc Baguelin & Samir Bhatt & Adhiratha Boonyasiri & Nicholas F. Brazeau & Lorenzo Cattarino & Laura V. Cooper & Helen Coupland &, 2021. "Reduction in mobility and COVID-19 transmission," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
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    1. Baudains, Peter & Kalatian, Arash & Choudhury, Charisma F. & Manley, Ed, 2024. "Social inequality and the changing patterns of travel in the pandemic and post-pandemic era," Journal of Transport Geography, Elsevier, vol. 118(C).
    2. MASUHARA Hiroaki & HOSOYA Kei, 2022. "What Impacts Do Human Mobility and Vaccination Have on Trends in COVID-19 Infections? Evidence from four developed countries," Discussion papers 22087, Research Institute of Economy, Trade and Industry (RIETI).
    3. Yi Liu & Tiantian Gu & Lingzhi Li & Peng Cui & Yan Liu, 2023. "Measuring the Urban Resilience Abased on Geographically Weighted Regression (GWR) Model in the Post-Pandemic Era: A Case Study of Jiangsu Province, China," Land, MDPI, vol. 12(7), pages 1-19, July.

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