Forecasting the outbreak of COVID-19 in Lebanon

Deeb, Omar El; Jalloul, Maya

doi:10.1101/2020.09.03.20187880

Cited by 8 publications

(11 citation statements)

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“…Previous forecasts on the number of cases in Lebanon has proven to be successful and the actual data were in range of expectations according to the models implemented [7]. This supports the motivation behind current forecasts in order to supply the decision makers with some estimates that are necessary for policy measures to be undertaken.…”

Section: Results and Conclusionsupporting

confidence: 53%

Note: Forecasting COVID-19 spread in Lebanon February 8-21,2021

Jalloul

2021

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This note implements an iterative method in order to predict the number of active cases with COVID-19, and consequently forecast the number of inpatients to hospitals and ICU in Lebanon according to different scenarios after end of the complete closure and curfew implemented between January 13 and February 7, 2021. The forecast predicts a decrease in the number of infections and people in need for hospitalization and ICU during the 2 weeks after the curfew (until February 21st), with varying extents depending on the subsequent commitment to mitigation measures, except for the case of a 2% absolute increase from the current rate of infection, which would bring back the numbers of cases back to a increasing trend.

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Section: Results and Conclusionsupporting

confidence: 53%

Note: Forecasting COVID-19 spread in Lebanon February 8-21,2021

Jalloul

2021

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“…Therefore, mitigation measures have been taken into effect early in March, while gradually being lifted as of 10 May. Yet, the activities in the airport were restarted at one-fifth capacity as of 1 July 2020 [ 7 ]. This fast action helped in the initial containment of the disease [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…Unexpectedly, after the massive Beirut's port explosion on 4 August that caused hundreds of deaths, thousands of injuries and destroyed half of the city's medical centres, the country witnessed a surge in COVID-19 infections. This urged the Lebanese authorities to impose a partial lockdown which included the closing of some businesses, banning public gatherings and enforcing midnight curfew [ 7 ]. However, the two-week lockdown was prematurely eased due to the economic crisis [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…that caused hundreds of deaths, thousands of injuries, and destroyed half of the city's medical centres, the country witnessed a surge in COVID-19 infections. This urged the Lebanese authorities to impose a partial lockdown which included the closing of some businesses, banning public gatherings, and enforcing midnight curfew(7). However, the two-week lockdown was prematurely eased due to the economic crisis(6).At the time of writing this paper, despite the https://doi.org/10.1017/S095026882100025X Downloaded from https://www.cambridge.org/core.…”

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confidence: 99%

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Challenge of forecasting demand of medical resources and supplies during a pandemic: A comparative evaluation of three surge calculators for COVID-19

et al. 2021

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Ever since the World Health Organization (WHO) declared the new coronavirus disease 2019 (COVID-19) as a pandemic, there has been a public health debate concerning medical resources and supplies including hospital beds, intensive care units (ICU), ventilators and protective personal equipment (PPE). Forecasting COVID-19 dissemination has played a key role in informing healthcare professionals and governments on how to manage overburdened healthcare systems. However, forecasting during the pandemic remained challenging and sometimes highly controversial. Here, we highlight this challenge by performing a comparative evaluation for the estimations obtained from three COVID-19 surge calculators under different social distancing approaches, taking Lebanon as a case study. Despite discrepancies in estimations, the three surge calculators used herein agree that there will be a relative shortage in the capacity of medical resources and a significant surge in PPE demand if the social distancing policy is removed. Our results underscore the importance of implementing containment interventions including social distancing in alleviating the demand for medical care during the COVID-19 pandemic in the absence of any medication or vaccine. The paper also highlights the value of employing several models in surge planning.

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“…The determination of the mean center of a population (centroid) was discussed in [21, 22, 23] and extending the concept to the determination of the mean center of wealth and infections allowed for a spatial analysis of the temporal dynamics of wealth distribution, economic growth and infectious diseases [24]. The dynamics of the outbreak of COVID-19 in Lebanon and its reproduction number dynamics were studied in [25, 26, 27].…”

Section: Introductionmentioning

confidence: 99%

Spatial autocorrelation and the dynamics of the mean center of COVID-19 infections in Lebanon

Deeb

2020

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In this paper we study the spatial spread of the COVID-19 infection in Lebanon. We inspect the spreading of the daily new infections across the 26 administrative districts of the country, and implement Moran's I statistics in order to analyze the tempo-spatial clustering of the infection in relation to various variables parameterized by adjacency, proximity, population, population density, poverty rate and poverty density, and we find out that except for the poverty rate, the spread of the infection is clustered and associated to those parameters with varying magnitude for the time span between July (geographic adjacency and proximity) or August (population, population density and poverty density) through October. We also determine the temporal dynamics of geographic location of the mean center of new and cumulative infections since late March. The results obtained allow for regionally and locally adjusted health policies and measures that would provide higher levels of public health safety in the country.

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Forecasting the outbreak of COVID-19 in Lebanon

Cited by 8 publications

References 1 publication

Note: Forecasting COVID-19 spread in Lebanon February 8-21,2021

Note: Forecasting COVID-19 spread in Lebanon February 8-21,2021

Challenge of forecasting demand of medical resources and supplies during a pandemic: A comparative evaluation of three surge calculators for COVID-19

Spatial autocorrelation and the dynamics of the mean center of COVID-19 infections in Lebanon

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