Role of modelling in COVID-19 policy development

McBryde, Emma S.; Meehan, Michael T.; Adegboye, Oyelola A.; Adekunle, Adeshina I.; Caldwell, Jamie M.; Pak, Anton; Rojas, Diana Patricia; Williams, Briony; Trauer, James M.

doi:10.1016/j.prrv.2020.06.013

Cited by 81 publications

(74 citation statements)

References 35 publications

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“…The preparedness and capacity of African countries to detect, respond and prevent infectious disease have been suggested to be low 28 , 29 . This may be complicated by the indirect effects associated with disruptions to other critical healthcare services due concurrent outbreaks in some African countries 30 .…”

Section: Resultsmentioning

confidence: 99%

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study

Adegboye

Adekunle

Pak

et al. 2021

Travel Medicine and Infectious Disease

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Background . The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 around the globe. Methods . Using data on the number of confirmed cases of COVID-19 and air travel data between countries, we applied a stochastic meta-population model to estimate the global spread of COVID-19. Pearson’s correlation, semi-variogram, and Moran’s Index were used to examine the association and spatial aucorretaion between the number of COVID-19 cases and travel influx (and arrival time) from the source country. Results . We found significant negative association between disease arrival time and number of cases imported from Italy (r= -0.43, p=0.004) and significant positive association between the number of COVID-19 cases and daily travel influx from Italy (r=0.39, p=0.011). Using bivariate Moran’s Index analysis, we found evidence of spatial interaction between COVID-19 cases and travel influx (Moran’s I=0.340). Asia-Pacific region is at higher/extreme risk of disease importation from the Chinese epicentre, whereas the rest of Europe, South-America and Africa are more at risk from the Italian epicentre. Conclusion . We showed that as the epicentre changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities.

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Section: Resultsmentioning

confidence: 99%

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study

Adegboye

Adekunle

Pak

et al. 2021

Travel Medicine and Infectious Disease

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“…Our data may also advise how to guide re-opening phases in Puerto Rico and serve as a reference for evaluating lockdown and quarantine measures in this vulnerable population. Lastly, with the current widespread vaccination efforts across the USA and in Puerto Rico, our approach can serve as reference data to model the impact of vaccination [27].…”

Section: Discussionmentioning

confidence: 99%

Modeling the Number of COVID-19 Confirmed Cases and Deaths in Puerto Rico: One-year Experience

El¹,

JC²,

Cm³

et al. 2021

austinbiomandbiostat

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Aims: To describe and project the number of COVID-19 cases and deaths reported in Puerto Rico, according to age and sex. Methods: We used surveillance data from March 8, 2020 to March 13, 2021 to describe and predict, by age and sex, the number of cases and deaths in Puerto Rico using Generalized Additive Models. The statistical modeling was performed in R software using the mgcv package. Results: The analytic sample consisted of 95,208 confirmed cases and 2,080 deaths reported by the Puerto Rico Department of Health until the second week of March 2021. The risk of COVID-19 infection was highest among adults aged 20-59 years, as compared with those younger than 20 years (RR20-39 vs. <20: 2.35 [95% CI: 1.80-3.06] and (RR20-59 vs. <20: 2.30 [95% CI: 1.76-3.00]). However, the pattern in the risk of death showed an inverse relationship: the highest risk of death occurred in adults 60 years and over as compared with those younger than 60 years (RR≥80 vs. <60: 22.4 [95% CI: 18.9-26.5] and (RR60-79 vs. <60: 6.7 [95% CI: 5.6-7.9]). Although there were no significant differences in the risk of infection (p>0.1) by sex, males had a 70% (95% CI: 50-100%) greater risk of death than their female counterparts. The projected weekly number of confirmed cases of COVID-19 showed a downward trend; we expected approximately 510 confirmed cases of COVID-19 in the week ending March 27, 2021. Similarly, the projected weekly number of COVID-19 deaths showed a downward trend. Conclusion: Future studies are needed to understand age and sex differences in COVID-19 infections and deaths. Increments in the number of COVID-19 cases in the short term are of great concern to justify more substantial preventive restrictions.

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“…In general, these models attempt to capture the combined interaction of a given viral epidemiology, the effects of relevant non-pharmaceutical interventions (NPIs), and the compliance of the public with these measures. They have guided much of the international policy response to COVID-19 (see McBryde et al 2020 and Thomson, 2020 ) and have even garnered wider public media attention beyond epidemiological research circles. In this respect, the main NPIs under discussion have related to physical distancing between individuals.…”

Section: Introductionmentioning

confidence: 99%

Incorporating Social Determinants of Health into Modelling of COVID-19 and other Infectious Diseases: A Baseline Socio-economic Compartmental Model

Galanis

Hanieh

2021

Social Science & Medicine

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The role of socio-economic conditions has been largely implicit in mathematical epidemiological models. However, measures to address the current pandemic, specifically the relevant interventions proposing physical distancing, have highlighted how social determinants affect contagion and mortality dynamics of COVID-19. For the most part, these social determinants are not present in either policy discussions or in relevant epidemiological models. We argue for the importance of incorporating relevant social determinants of health into the modelling dynamics of COVID-19, and show how global variation of these conditions may be integrated into relevant models. In doing so, we also highlight a key political economy aspect of reproduction dynamics in epidemics.

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Role of modelling in COVID-19 policy development

Abstract: Modelling COVID-19 influenced policy at all stages of the outbreak. Greater synthesis of epidemiological models and economic models is needed to assist policy makers. Models must be adapted to context, both in terms of disease behaviour and different interventions in different countries.

Cited by 81 publications

References 35 publications

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study

Modeling the Number of COVID-19 Confirmed Cases and Deaths in Puerto Rico: One-year Experience

Incorporating Social Determinants of Health into Modelling of COVID-19 and other Infectious Diseases: A Baseline Socio-economic Compartmental Model

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