» Articles » PMID: 36962513

Association Between Mobility, Non-pharmaceutical Interventions, and COVID-19 Transmission in Ghana: A Modelling Study Using Mobile Phone Data

Abstract

Governments around the world have implemented non-pharmaceutical interventions to limit the transmission of COVID-19. Here we assess if increasing NPI stringency was associated with a reduction in COVID-19 cases in Ghana. While lockdowns and physical distancing have proven effective for reducing COVID-19 transmission, there is still limited understanding of how NPI measures are reflected in indicators of human mobility. Further, there is a lack of understanding about how findings from high-income settings correspond to low and middle-income contexts. In this study, we assess the relationship between indicators of human mobility, NPIs, and estimates of Rt, a real-time measure of the intensity of COVID-19 transmission. We construct a multilevel generalised linear mixed model, combining local disease surveillance data from subnational districts of Ghana with the timing of NPIs and indicators of human mobility from Google and Vodafone Ghana. We observe a relationship between reductions in human mobility and decreases in Rt during the early stages of the COVID-19 epidemic in Ghana. We find that the strength of this relationship varies through time, decreasing after the most stringent period of interventions in the early epidemic. Our findings demonstrate how the association of NPI and mobility indicators with COVID-19 transmission may vary through time. Further, we demonstrate the utility of combining local disease surveillance data with large scale human mobility data to augment existing surveillance capacity to monitor the impact of NPI policies.

Citing Articles

Bias in mobility datasets drives divergence in modeled outbreak dynamics.

Chin T, Johansson M, Chowdhury A, Chowdhury S, Hosan K, Quader M Commun Med (Lond). 2025; 5(1):8.

PMID: 39774250 PMC: 11706981. DOI: 10.1038/s43856-024-00714-5.


Public health research using cell phone derived mobility data in sub-Saharan Africa: Ethical issues.

Rennie S, Atuire C, Mtande T, Jaoko W, Litewka S, Juengst E S Afr J Sci. 2024; 119(5-6).

PMID: 39328369 PMC: 11426410. DOI: 10.17159/sajs.2023/14777.


Decreased influenza activity during the COVID-19 pandemic in Ghana, 2020.

Asante I, Nyarko S, Awuku-Larbi Y, Obeng R, Sarpong G, Amenuvor E Front Public Health. 2024; 11:1290553.

PMID: 38292380 PMC: 10824892. DOI: 10.3389/fpubh.2023.1290553.


Changes in mobility patterns during the COVID-19 pandemic in Zambia: Implications for the effectiveness of NPIs in Sub-Saharan Africa.

Loisate S, Mutembo S, Arambepola R, Makungo K, Kabalo E, Sinyange N PLOS Glob Public Health. 2023; 3(10):e0000892.

PMID: 37906535 PMC: 10617722. DOI: 10.1371/journal.pgph.0000892.


Phylodynamic analysis revealed that human mobility and vaccination were correlated to the local spread of SARS-CoV-2 in Republic of Korea.

Lee S, Lee D, Kim J, Kim D, Kim J, Kim J Emerg Microbes Infect. 2023; 12(2):2228934.

PMID: 37345516 PMC: 10324436. DOI: 10.1080/22221751.2023.2228934.


References
1.
Wesolowski A, Eagle N, Tatem A, Smith D, Noor A, Snow R . Quantifying the impact of human mobility on malaria. Science. 2012; 338(6104):267-70. PMC: 3675794. DOI: 10.1126/science.1223467. View

2.
Grantz K, Meredith H, Cummings D, Metcalf C, Grenfell B, Giles J . The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology. Nat Commun. 2020; 11(1):4961. PMC: 7528106. DOI: 10.1038/s41467-020-18190-5. View

3.
Marshall J, Wu S, Sanchez C H, Kiware S, Ndhlovu M, Ouedraogo A . Mathematical models of human mobility of relevance to malaria transmission in Africa. Sci Rep. 2018; 8(1):7713. PMC: 5955928. DOI: 10.1038/s41598-018-26023-1. View

4.
Nouvellet P, Bhatia S, Cori A, Ainslie K, Baguelin M, Bhatt S . Reduction in mobility and COVID-19 transmission. Nat Commun. 2021; 12(1):1090. PMC: 7889876. DOI: 10.1038/s41467-021-21358-2. View

5.
Badr H, Du H, Marshall M, Dong E, Squire M, Gardner L . Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study. Lancet Infect Dis. 2020; 20(11):1247-1254. PMC: 7329287. DOI: 10.1016/S1473-3099(20)30553-3. View