COVID-19 most vulnerable Mexican cities lack the public health infrastructure to face the pandemic: a new temporally-explicit model

Dáttilo, Wesley; Silva, Alcides Castro e; Guevara, Roger; MacGregor-Fors, Ian; Ribeiro, Sérvio Pontes

doi:10.1101/2020.04.10.20061192

Cited by 10 publications

(13 citation statements)

References 12 publications

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“…It is projected that the state of healthcare infrastructure in developing countries like South Africa exposes such healthcare systems therein to being easily overwhelmed if an exponential increase in the number of COVID-19 cases is experienced [ 5 , 8 , 9 ]. This understanding and the need to manage the rate of infections across the globe culminated in the lockdown of various economies, thereby resulting in movement restrictions, social distancing, deployment of rapid testing platforms and contact tracing.…”

Section: Introductionmentioning

confidence: 99%

Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing

Agbehadji

Awuzie

Ngowi

et al. 2020

IJERPH

200

112

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The emergence of the 2019 novel coronavirus (COVID-19) which was declared a pandemic has spread to 210 countries worldwide. It has had a significant impact on health systems and economic, educational and social facets of contemporary society. As the rate of transmission increases, various collaborative approaches among stakeholders to develop innovative means of screening, detecting and diagnosing COVID-19’s cases among human beings at a commensurate rate have evolved. Further, the utility of computing models associated with the fourth industrial revolution technologies in achieving the desired feat has been highlighted. However, there is a gap in terms of the accuracy of detection and prediction of COVID-19 cases and tracing contacts of infected persons. This paper presents a review of computing models that can be adopted to enhance the performance of detecting and predicting the COVID-19 pandemic cases. We focus on big data, artificial intelligence (AI) and nature-inspired computing (NIC) models that can be adopted in the current pandemic. The review suggested that artificial intelligence models have been used for the case detection of COVID-19. Similarly, big data platforms have also been applied for tracing contacts. However, the nature-inspired computing (NIC) models that have demonstrated good performance in feature selection of medical issues are yet to be explored for case detection and tracing of contacts in the current COVID-19 pandemic. This study holds salient implications for practitioners and researchers alike as it elucidates the potentials of NIC in the accurate detection of pandemic cases and optimized contact tracing.

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Section: Introductionmentioning

confidence: 99%

Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing

Agbehadji

Awuzie

Ngowi

et al. 2020

IJERPH

200

112

View full text Add to dashboard Cite

show abstract

“…These results demonstrate that social distancing could have a dramatic impact on reducing the number of infected people in Mexico, which is consistent with other studies. A study predicting the vulnerability of fifty Mexican cities found that a 45% adherence to social distancing could reduce the number of infected people by up to 78.7% [43]. While modeled data are useful in planning for health system needs, other countries have begun to measure the true impact of social distancing measures using interrupted time series analyses.…”

Section: Plos Onementioning

confidence: 99%

Projected impact of COVID-19 mitigation strategies on hospital services in the Mexico City Metropolitan Area

et al. 2020

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Evidence-based models may assist Mexican government officials and health authorities in determining the safest plans to respond to the coronavirus disease 2019 (COVID-19) pandemic in the most-affected region of the country, the Mexico City Metropolitan Area. This study aims to present the potential impacts of COVID-19 in this region and to model possible benefits of mitigation efforts. The COVID-19 Hospital Impact Model for Epidemics was used to estimate the probable evolution of COVID-19 in three scenarios: (i) no social distancing, (ii) social distancing in place at 50% effectiveness, and (iii) social distancing in place at 60% effectiveness. Projections of the number of inpatient hospitalizations, intensive care unit admissions, and patients requiring ventilators were made for each scenario. Using the model described, it was predicted that peak case volume at 0% mitigation was to occur on April 30, 2020 at 11,553,566 infected individuals. Peak case volume at 50% mitigation was predicted to occur on June 1, 2020 with 5,970,093 infected individuals and on June 21, 2020 for 60% mitigation with 4,128,574 infected individuals. Occupancy rates in hospitals during peak periods at 0%, 50%, and 60% mitigation would be 875.9%, 322.8%, and 203.5%, respectively, when all inpatient beds are included. Under these scenarios, peak daily hospital admissions would be 40,438, 13,820, and 8,650. Additionally, 60% mitigation would result in a decrease in peak intensive care beds from 94,706 to 23,116 beds and a decrease in peak ventilator need from 67,889 to 17,087 units. Mitigating the spread of COVID-19 through social distancing could have a dramatic impact on reducing the number of infected people and minimize hospital overcrowding. These evidence-based models may enable careful resource utilization and encourage targeted public health responses.

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“…Complaints were particularly mentioned in Nigeria -where the upper class usually goes for medical treatment to HICs [49], but also in Colombia [9], Nepal 9,10 , and even Mexico. 30 The shortage of ICU-beds and of protective clothing was reported in all countries [82,46] but also the construction of provisional treatment units. 8,31 Alternative approaches in South Korea and Kerala/India…”

Section: Vii) Impact On Peoples` Creativity (Survival Strategies)mentioning

confidence: 99%

“…Violent acts of vandalism have been reported, where food trucks were looted (Nigeria [81] and Colombia21 ) or food vendors were attacked by the hungry crowd. An aggravating fact is that in many countries people in the informal sector have no medical insurance (India[30] and Nepal[58]) and cannot receive medical treatment. iii) Impact on migrant workers and refugees Migrant workers or refugees are particularly vulnerable in the containment strategy.…”

mentioning

confidence: 99%

The covid-19 pandemic in Low- and Middle-Income Countries, who carries the burden? Review of mass media and publications from six countries

Chackalackal

Al-Aghbari

Jang

et al. 2020

Preprint

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Rich countries used in the Covid-19 pandemic lockdown and physical distancing policies for transmission control. However, are these measures also suitable in countries with a fragile economy resting mainly on the informal sector? The impact of lockdown measures in disadvantaged population strata in six Low- and Middle-Income Countries (LMICs) was reviewed using i) systematic review of 17 published papers and ii) review of 90 media reports. Those who most suffered from the lockdown were migrants, workers in the informal sector (which is huge), small businesses, slum dwellers, women and elderly revealing the social, cultural and economic inequalities of societies. Financial and food support for the poor was inadequate and sometimes mismanaged. In the better organized societies, the resilience was stronger (South Korea, Kerala/India) but also here the poor had to suffer most. It is strongly recommended that outbreak response strategies should particularly focus on the poor and vulnerable population.

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COVID-19 most vulnerable Mexican cities lack the public health infrastructure to face the pandemic: a new temporally-explicit model

Abstract: 22

Cited by 10 publications

References 12 publications

Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing

Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing

Projected impact of COVID-19 mitigation strategies on hospital services in the Mexico City Metropolitan Area

The covid-19 pandemic in Low- and Middle-Income Countries, who carries the burden? Review of mass media and publications from six countries

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