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Ege F. Short, stringent lockdowns halted SARS-CoV-2 transmissions in Danish municipalities. Sci Rep 2024; 14:18712. [PMID: 39134618 PMCID: PMC11319722 DOI: 10.1038/s41598-024-68929-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 07/30/2024] [Indexed: 08/15/2024] Open
Abstract
In late 2020, the focus of the global effort against the COVID-19 pandemic centered around the development of a vaccine, when reports of a mutated SARS-CoV-2 virus variant in a population of 17 million farmed mink came from Denmark, threatening to jeopardize this effort. Spillover infections of the new variant between mink and humans were feared to threaten the efficacy of upcoming vaccines. In this study the ensuing short-lived yet stringent lockdowns imposed in 7 of the countries 98 municipalities are analysed for their effectiveness to reduce SARS-CoV-2 infections. Synthetic counterfactuals are created for each of these municipalities using a weighted average combination of the remaining municipalities not targeted by the stringent measures. This allows for a clear overview regarding the development of test-positivity rates, citizen mobility behaviours and lastly daily infection numbers in response to the restrictions. The findings show that these targeted, short-term lockdowns significantly curtailed further infections, demonstrating a marked decrease, first in citizens mobility and then in daily cases when compared to their synthetic counterfactuals. Overall, the estimates indicate average reductions to infection numbers to be around 31%. This study underscores the potential of strict, yet severe lockdowns in breaking ongoing infection dynamics, by utilising a rare quasi-experimental design case that avoids bias introduced through treatment selection.
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Affiliation(s)
- Florian Ege
- Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Odense, Denmark.
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2
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Dhaliwal JS, Sekhon MS, Rajotia A, Dang AK, Singh PP, Bilal M, Sakthivel H, Ahmed R, Verma R, Ramphul K, Sethi PS. Disparities and Outcomes in the First and Second Year of the Pandemic on Events of Acute Myocardial Infarction in Coronavirus Disease 2019 Patients. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:597. [PMID: 38674243 PMCID: PMC11052327 DOI: 10.3390/medicina60040597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 03/29/2024] [Accepted: 04/02/2024] [Indexed: 04/28/2024]
Abstract
Background and Objectives: Coronavirus disease 2019 (COVID-19) caused several cardiovascular complications, including acute myocardial infarction (AMI), in infected patients. This study aims to understand the overall trends of AMI among COVID-19 patients during the first two years of the pandemic and the disparities and outcomes between the first and second years. Materials and Methods: The retrospective analysis was conducted via the 2020 and 2021 National Inpatient Sample (NIS) database for hospitalizations between April 2020 and December 2021 being analyzed for adults with a primary diagnosis of COVID-19 who experienced events of AMI. A comparison of month-to-month events of AMI and mortality of AMI patients with concomitant COVID-19 was made alongside their respective patient characteristics. Results: Out of 2,541,992 COVID-19 hospitalized patients, 3.55% experienced AMI. The highest rate of AMI was in December 2021 (4.35%). No statistical differences in trends of AMI mortality were noted over the 21 months. AMI cases in 2021 had higher odds of undergoing PCI (aOR 1.627, p < 0.01). They experienced higher risks of acute kidney injury (aOR 1.078, p < 0.01), acute ischemic stroke (aOR 1.215, p < 0.01), cardiac arrest (aOR 1.106, p < 0.01), need for mechanical ventilation (aOR 1.133, p < 0.01), and all-cause mortality (aOR 1.032, 95% CI 1.001-1.064, p = 0.043). Conclusions: The incidence of AMI among COVID-19 patients fluctuated over the 21 months of this study, with a peak in December 2021. COVID-19 patients reporting AMI in 2021 experienced higher overall odds of multiple complications, which could relate to the exhaustive burden of the pandemic in 2021 on healthcare, the changing impact of the virus variants, and the hesitancy of infected patients to seek care.
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Affiliation(s)
- Jasninder Singh Dhaliwal
- Department of Internal Medicine, University of California Riverside School of Medicine, Riverside, CA 92521, USA
| | - Manraj S. Sekhon
- Department of Internal Medicine, University of California Riverside School of Medicine, Riverside, CA 92521, USA
| | - Arush Rajotia
- Department of Internal Medicine, University of California Riverside School of Medicine, Riverside, CA 92521, USA
| | - Ashujot K. Dang
- Department of Internal Medicine, University of California Riverside School of Medicine, Riverside, CA 92521, USA
| | - Prabh Partap Singh
- School of Medicine, University of California Riverside School of Medicine, Riverside, CA 92521, USA
| | - Maham Bilal
- Department of Internal Medicine, Dow University of Health Sciences, Karachi 74200, Pakistan
| | - Hemamalini Sakthivel
- One Brooklyn Health System/Interfaith Medical Ctr Program, Brooklyn, NY 11213, USA
| | - Raheel Ahmed
- Royal Brompton Hospital, Part of Guy’s and St. Thomas’ NHS Foundation Trust, London SW3 6NP, UK
| | - Renuka Verma
- Department of Internal Medicine, Kirk Kerkorian School of Medicine at UNLV, Las Vegas, NV 89154, USA
| | | | - Prabhdeep S. Sethi
- Department of Internal Medicine, University of California Riverside School of Medicine, Riverside, CA 92521, USA
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Krajewski T, Hudgens M. The augmented synthetic control method in public health and biomedical research. Stat Methods Med Res 2024; 33:376-391. [PMID: 38320801 PMCID: PMC10981189 DOI: 10.1177/09622802231224638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
Estimating treatment (or policy or intervention) effects on a single individual or unit has become increasingly important in health and biomedical sciences. One method to estimate these effects is the synthetic control method, which constructs a synthetic control, a weighted average of control units that best matches the treated unit's pre-treatment outcomes and other relevant covariates. The intervention's impact is then estimated by comparing the post-intervention outcomes of the treated unit and its synthetic control, which serves as a proxy for the counterfactual outcome had the treated unit not experienced the intervention. The augmented synthetic control method, a recent adaptation of the synthetic control method, relaxes some of the synthetic control method's assumptions for broader applicability. While synthetic controls have been used in a variety of fields, their use in public health and biomedical research is more recent, and newer methods such as the augmented synthetic control method are underutilized. This paper briefly describes the synthetic control method and its application, explains the augmented synthetic control method and its differences from the synthetic control method, and estimates the effects of an antimalarial initiative in Mozambique using both the synthetic control method and the augmented synthetic control method to highlight the advantages of using the augmented synthetic control method to analyze the impact of interventions implemented in a single region.
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Affiliation(s)
- Taylor Krajewski
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
| | - Michael Hudgens
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
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Touchton M, Knaul FM, Arreola-Ornelas H, Porteny T, Carniado ÓM, Faganello M, Hummel C, Otero S, Insua J, Patino F, Undurraga E, Pérez-Cruz P, Sanchez-Talanquer M, Velasco Guachalla VX, Nelson-Nuñez J, Boulding C, Calderon-Anyosa R, Garcia PJ, Vargas Enciso V. Non-pharmaceutical interventions to combat COVID-19 in the Americas described through daily sub-national data. Sci Data 2023; 10:734. [PMID: 37865630 PMCID: PMC10590388 DOI: 10.1038/s41597-023-02638-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 10/12/2023] [Indexed: 10/23/2023] Open
Abstract
This dataset covers national and subnational non-pharmaceutical interventions (NPI) to combat the COVID-19 pandemic in the Americas. Prior to the development of a vaccine, NPI were governments' primary tools to mitigate the spread of COVID-19. Variation in subnational responses to COVID-19 is high and is salient for health outcomes. This dataset captures governments' dynamic, varied NPI to combat COVID-19 for 80% of Latin America's population from each country's first case through December 2021. These daily data encompass all national and subnational units in Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, and Peru. The dataset includes individual and aggregate indices of nine NPI: school closures, work suspensions, public event cancellations, public transport suspensions, information campaigns, local travel restrictions, international travel controls, stay-at-home orders, and restrictions on the size of gatherings. We also collected data on mask mandates as a separate indicator. Local country-teams drew from multiple data sources, resulting in high-quality, reliable data. The dataset thus allows for consistent, meaningful comparisons of NPI within and across countries during the pandemic.
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Affiliation(s)
- Michael Touchton
- Department of Political Science, School of Arts and Sciences, University of Miami, Miami, Florida, USA
- Institute for Advanced Study of the Americas, University of Miami, Miami, Florida, USA
| | - Felicia Marie Knaul
- Institute for Advanced Study of the Americas, University of Miami, Miami, Florida, USA
- Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, USA
- Tómatelo a Pecho, A.C., Mexico City, Mexico
- Fundación Mexicana para la Salud, A.C., Mexico City, Mexico
| | - Héctor Arreola-Ornelas
- Institute for Advanced Study of the Americas, University of Miami, Miami, Florida, USA.
- Tómatelo a Pecho, A.C., Mexico City, Mexico.
- Fundación Mexicana para la Salud, A.C., Mexico City, Mexico.
- Institute for Obesity Research, Tecnológico de Monterrey, Monterrey, Mexico.
- School of Government and Public Transformation, Tecnológico de Monterrey, Mexico City, Mexico.
| | - Thalia Porteny
- Institute for Advanced Study of the Americas, University of Miami, Miami, Florida, USA
- Department of Health Policy and Management, Columbia Mailman School of Public Health, New York, New York, USA
| | - Óscar Méndez Carniado
- Institute for Advanced Study of the Americas, University of Miami, Miami, Florida, USA
- Tómatelo a Pecho, A.C., Mexico City, Mexico
- Institute for Obesity Research, Tecnológico de Monterrey, Monterrey, Mexico
| | - Marco Faganello
- MAF dataScience, Universidade Estadual de Campinas, Campinas, Brazil
| | - Calla Hummel
- Department of Political Science, School of Arts and Sciences, University of Miami, Miami, Florida, USA
| | - Silvia Otero
- Facultad de Estudios Internacionales, Políticos y Urbanos, Universidad del Rosario, Bogotá, Colombia
| | - Jorge Insua
- Health Policy and Management, School of Biomedical Sciences, School of Government, School of Health Care Management, Universidad Austral, Buenos Aires, Argentina
- School of Public Health, University of Buenos Aires, Buenos Aires, Argentina
| | | | - Eduardo Undurraga
- Escuela de Gobierno, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Pedro Pérez-Cruz
- Departamento Medicina Interna, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
- Millennium Nucleus for the Study of the Life Course and Vulnerability, Santiago, Chile
| | | | | | - Jami Nelson-Nuñez
- Department of Political Science, University of New Mexico, Albuquerque, New Mexico, USA
| | - Carew Boulding
- Department of Political Science, University of Colorado, Boulder, Colorado, USA
| | - Renzo Calderon-Anyosa
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Patricia J Garcia
- Universidad Peruana Cayetano Heredia, Lima, San Martin de Porres, Peru
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Murphy C, Lim WW, Mills C, Wong JY, Chen D, Xie Y, Li M, Gould S, Xin H, Cheung JK, Bhatt S, Cowling BJ, Donnelly CA. Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2023; 381:20230132. [PMID: 37611629 PMCID: PMC10446910 DOI: 10.1098/rsta.2023.0132] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 05/23/2023] [Indexed: 08/25/2023]
Abstract
Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.
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Affiliation(s)
- Caitriona Murphy
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Wey Wen Lim
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Cathal Mills
- Department of Statistics, University of Oxford, Oxford, UK
| | - Jessica Y. Wong
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Dongxuan Chen
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong, People's Republic of China
| | - Yanmy Xie
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Mingwei Li
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong, People's Republic of China
| | - Susan Gould
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
- Tropical and Infectious Disease Unit, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Hualei Xin
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Justin K. Cheung
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Samir Bhatt
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Kobenhavn, Denmark
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Benjamin J. Cowling
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong, People's Republic of China
| | - Christl A. Donnelly
- Department of Statistics, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
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Ambade PN, Thavorn K, Pakhale S. COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India? Healthcare (Basel) 2023; 11:2112. [PMID: 37510552 PMCID: PMC10379405 DOI: 10.3390/healthcare11142112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 06/29/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023] Open
Abstract
INTRODUCTION Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs. METHODS Using daily case data for 84 days (9 March-31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R0), daily reproduction number (Re), and case doubling time. Based on pre-restriction and Phase 1 R0, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis. RESULTS The estimated median R0 during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, -15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, -204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83). CONCLUSION Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.
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Affiliation(s)
- Preshit Nemdas Ambade
- Department of Population Health Sciences, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Kednapa Thavorn
- Faculty of Medicine, School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON K1G 5Z3, Canada
| | - Smita Pakhale
- Faculty of Medicine, School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON K1G 5Z3, Canada
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Kuzmanic D, Valenzuela JP, Claro S, Canales A, Cerda D, Undurraga EA. Socioeconomic disparities in the reopening of schools during the pandemic in Chile. INTERNATIONAL JOURNAL OF EDUCATIONAL DEVELOPMENT 2023; 100:102805. [PMID: 37235200 PMCID: PMC10199314 DOI: 10.1016/j.ijedudev.2023.102805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 03/14/2023] [Accepted: 05/02/2023] [Indexed: 05/28/2023]
Abstract
The COVID-19 pandemic produced the most significant disruption in education in history. More than 190 countries suspended in-person instruction, affecting an estimated 1.6 billion students. The reopening of schools has been unequal. Schools in more affluent areas reopened sooner than poorer ones, exacerbating preexisting inequalities. There is limited research about the reopening processes in Latin America, where schools were closed for extended periods. Using a rich administrative dataset, we investigate the gaps in the resumption of in-person instruction in Chilean schools across socioeconomic groups in the fall of 2021. Schools with lower socioeconomic status were significantly less likely to offer in-person instruction. Disparities in reopening decisions were associated with administrative factors rather than economic or local epidemiological conditions.
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Affiliation(s)
- Danilo Kuzmanic
- Center for Advanced Research in Education, Institute of Education, Universidad de Chile, Chile
| | - Juan Pablo Valenzuela
- Center for Advanced Research in Education, Institute of Education, Universidad de Chile, Chile
| | - Susana Claro
- Escuela de Gobierno, Pontificia Universidad Católica de Chile, Chile
| | - Andrea Canales
- Instituto de Sociología, Facultad de Ciencias Sociales, Pontificia Universidad Católica de Chile, Chile
| | - Daniela Cerda
- Escuela de Gobierno, Pontificia Universidad Católica de Chile, Chile
| | - Eduardo A Undurraga
- Escuela de Gobierno, Pontificia Universidad Católica de Chile, Chile
- Canadian Institute for Advanced Research, Azrieli Global Scholars Program, CIFAR, Toronto, Canada
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Polwiang S. The lockdown and vaccination distribution in Thailand's COVID-19 epidemic: A model study. Infect Dis Model 2023; 8:551-561. [PMID: 37275749 PMCID: PMC10225064 DOI: 10.1016/j.idm.2023.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 05/15/2023] [Accepted: 05/16/2023] [Indexed: 06/07/2023] Open
Abstract
Background Several countries used varied degrees of social isolation measures in response to the COVID-19 outbreak. In 2021, the lockdown in Thailand began on July 20 and lasted for the following six weeks. The lockdown has extremely detrimental effects on the economy and society, even though it may reduce the number of COVID-19 instances. Our goals are to assess the impact of the lockdown policy, the commencement time of lockdown, and the vaccination rate on the number of COVID-19 cases in Thailand in 2021. Methods We modeled the dynamics of COVID-19 in Thailand throughout 2021 using the SEIR model. The Google Mobility Index, vaccine distribution rate, and lockdown were added to the model. The Google Mobility Index represents the movement of individuals during a pandemic and shows how people react to lockdown. The model also examines the effect of vaccination rate on the incidence of COVID-19. Results The modeling approach demonstrates that a 6-week lockdown decreases the incidence number of COVID-19 by approximately 15.49-18.17%, depending on the timing of the lockdown compared to a non-lockdown scenario. An increasing vaccination rate potentially reduce the incidence number of COVID-19 by 5.12-18.35% without launching a lockdown. Conclusion Lockdowns can be an effective method to slow down the spread of COVID-19 when the vaccination program is not fully functional. When the vaccines are easily accessible on a large scale, the lockdown may terminated.
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Affiliation(s)
- Sittisede Polwiang
- Department of Mathematics, Faculty of Science, Silpakorn University, Nakhon Pathom, 73000, Thailand
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Pezoa R, Basso F, Quilodrán P, Varas M. Estimation of trip purposes in public transport during the COVID-19 pandemic: The case of Santiago, Chile. JOURNAL OF TRANSPORT GEOGRAPHY 2023; 109:103594. [PMID: 37123884 PMCID: PMC10121142 DOI: 10.1016/j.jtrangeo.2023.103594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 03/15/2023] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
The COVID-19 pandemic strongly affected the mobility of people. Several studies have quantified these changes, for example, measuring the effectiveness of quarantine measures and calculating the decrease in the use of public transport. Regarding the latter, however, a low level of understanding persists as to how the pandemic affected the distribution of trip purposes, hindering the design of policies aimed at increasing the demand for public transport in a post-pandemic era. To address this gap, in this article, we study how the purposes of trips made by public transport evolved during the COVID-19 pandemic in the city of Santiago, Chile. For this, we develop an XGBoost model using the latest available origin-destination survey as input. The calibrated model is applied to the information from smart payment cards during one week in 2018, 2020, and 2021. The results show that during the week of maximum restriction, that is, during 2020, the distribution of trips by purpose varied considerably, with the proportion of trips to work increasing, recreational trips decreasing, and trips for health purposes remaining unchanged. In sociodemographic terms, in the higher-income communes, the decrease in the proportion of trips for work purposes was much greater than that in the communes with lower income. Finally, with the gradual return to in-person activities in 2021, the distribution of trip purposes returned to values similar to those before the pandemic, although with a lower total amount, which suggests that unless relevant measures are taken, the low use of public transportation could be permanent.
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Affiliation(s)
- Raúl Pezoa
- Escuela de Ingeniería Industrial, Universidad Diego Portales, Santiago, Chile
| | - Franco Basso
- School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
- Instituto Sistemas Complejos de Ingeniería, Chile
| | - Paulina Quilodrán
- Escuela de Ingeniería Industrial, Universidad Diego Portales, Santiago, Chile
| | - Mauricio Varas
- Centro de Investigación en Sustentabilidad y Gestión Estratégica de Recursos, Facultad de Ingeniería, Universidad del Desarrollo, Santiago, Chile
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de Miguel Arribas A, Aleta A, Moreno Y. Assessing the effectiveness of perimeter lockdowns as a response to epidemics at the urban scale. Sci Rep 2023; 13:4474. [PMID: 36934138 PMCID: PMC10024032 DOI: 10.1038/s41598-023-31614-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/14/2023] [Indexed: 03/20/2023] Open
Abstract
From September 2020 to May 2021 Madrid region (Spain) followed a rather unique non-pharmaceutical intervention (NPI) by establishing a strategy of perimeter lockdowns (PLs) that banned travels to and from areas satisfying certain epidemiological risk criteria. PLs were pursued to avoid harsher restrictions, but some studies have found that the particular implementation by Madrid authorities was rather ineffective. Based on Madrid's case, we devise a general, minimal framework to investigate the PLs effectiveness by using a data-driven metapopulation epidemiological model of a city, and explore under which circumstances the PLs could be a good NPI. The model is informed with real mobility data from Madrid to contextualize its results, but it can be generalized elsewhere. The lowest lockdown activation threshold [Formula: see text] considered (14-day cumulative incidence rate of 20 cases per every [Formula: see text] inhabitants) shows a prevalence reduction [Formula: see text] with respect to the scenario [Formula: see text], more akin to the case of Madrid, and assuming no further mitigation. Only the combination of [Formula: see text] and mobility reduction [Formula: see text] can avoid PLs for more than [Formula: see text] of the system. The combination of low [Formula: see text] and strong local transmissibility reduction is key to minimize the impact, but the latter is harder to achieve given that we assume a situation with highly mitigated transmission, resembling the one observed during the second wave of COVID-19 in Madrid. Thus, we conclude that a generalized lockdown is hard to avoid under any realistic setting if only this strategy is applied.
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Affiliation(s)
- Alfonso de Miguel Arribas
- Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018, Zaragoza, Spain.
- Department of Theoretical Physics, University of Zaragoza, 50018, Zaragoza, Spain.
| | - Alberto Aleta
- Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018, Zaragoza, Spain
- Department of Theoretical Physics, University of Zaragoza, 50018, Zaragoza, Spain
| | - Yamir Moreno
- Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018, Zaragoza, Spain
- Department of Theoretical Physics, University of Zaragoza, 50018, Zaragoza, Spain
- Centai, Turin, Italy
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Salinas DG, Bustamante ML, Gallardo MO. Modelling quarantine effects on SARS-CoV-2 epidemiological dynamics in Chilean communes and their relationship with the Social Priority Index. PeerJ 2023; 11:e14892. [PMID: 36923504 PMCID: PMC10010178 DOI: 10.7717/peerj.14892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 01/23/2023] [Indexed: 03/12/2023] Open
Abstract
Background An epidemiological model (susceptible, un-quarantined infected, quarantined infected, confirmed infected (SUQC)) was previously developed and applied to incorporate quarantine measures and calculate COVID-19 contagion dynamics and pandemic control in some Chinese regions. Here, we generalized this model to incorporate the disease recovery rate and applied our model to records of the total number of confirmed cases of people infected with the SARS-CoV-2 virus in some Chilean communes. Methods In each commune, two consecutive stages were considered: a stage without quarantine and an immediately subsequent quarantine stage imposed by the Ministry of Health. To adjust the model, typical epidemiological parameters were determined, such as the confirmation rate and the quarantine rate. The latter allowed us to calculate the reproduction number. Results The mathematical model adequately reproduced the data, indicating a higher quarantine rate when quarantine was imposed by the health authority, with a corresponding decrease in the reproduction number of the virus down to values that prevent or decrease its exponential spread. In general, during this second stage, the communes with the lowest social priority indices had the highest quarantine rates, and therefore, the lowest effective viral reproduction numbers. This study provides useful evidence to address the health inequity of pandemics. The mathematical model applied here can be used in other regions or easily modified for other cases of infectious disease control by quarantine.
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Affiliation(s)
- Dino G Salinas
- Centro de Investigación Biomédica, Facultad de Medicina, Universidad Diego Portales, Santiago, Chile
| | - M Leonor Bustamante
- Human Genetics Program, Biomedical Sciences Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile.,Department of Psychiatry and Mental Health, North Division, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Mauricio O Gallardo
- Centro de Investigación Biomédica, Facultad de Medicina, Universidad Diego Portales, Santiago, Chile
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12
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Zivich PN, Hudgens MG, Brookhart MA, Moody J, Weber DJ, Aiello AE. Targeted maximum likelihood estimation of causal effects with interference: A simulation study. Stat Med 2022; 41:4554-4577. [PMID: 35852017 PMCID: PMC9489667 DOI: 10.1002/sim.9525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 06/20/2022] [Accepted: 06/28/2022] [Indexed: 11/08/2022]
Abstract
Interference, the dependency of an individual's potential outcome on the exposure of other individuals, is a common occurrence in medicine and public health. Recently, targeted maximum likelihood estimation (TMLE) has been extended to settings of interference, including in the context of estimation of the mean of an outcome under a specified distribution of exposure, referred to as a policy. This paper summarizes how TMLE for independent data is extended to general interference (network-TMLE). An extensive simulation study is presented of network-TMLE, consisting of four data generating mechanisms (unit-treatment effect only, spillover effects only, unit-treatment and spillover effects, infection transmission) in networks of varying structures. Simulations show that network-TMLE performs well across scenarios with interference, but issues manifest when policies are not well-supported by the observed data, potentially leading to poor confidence interval coverage. Guidance for practical application, freely available software, and areas of future work are provided.
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Affiliation(s)
- Paul N Zivich
- Department of Epidemiology, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, UNC Chapel Hill, Chapel Hill, North Carolina, USA
| | - Michael G Hudgens
- Department of Biostatistics, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, North Carolina, USA
| | - Maurice A Brookhart
- NoviSci, Durham, North Carolina, USA
- Department of Population Health Sciences, Duke University, Durham, North Carolina, USA
| | - James Moody
- Department of Sociology, Duke University, Durham, North Carolina, USA
| | - David J Weber
- Division of Infectious Diseases, Department of Medicine, UNC Chapel Hill, Chapel Hill, North Carolina, USA
| | - Allison E Aiello
- Department of Epidemiology, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, UNC Chapel Hill, Chapel Hill, North Carolina, USA
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