Epidemiologia

Research

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21 pages, 6710 KiB

Open AccessArticle

Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021

by Sushma Dahal, Ruiyan Luo, Raj Kumar Subedi, Meghnath Dhimal and Gerardo Chowell

Epidemiologia 2021, 2(4), 639-659; https://doi.org/10.3390/epidemiologia2040043 - 16 Dec 2021

Cited by 7 | Viewed by 3988

Abstract

Nepal was hard hit by a second wave of COVID-19 from April–May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 [...] Read more.

Nepal was hard hit by a second wave of COVID-19 from April–May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week sequential forecasts of 10-days and 20-days at national level using three dynamic phenomenological growth models from 5 March 2021–22 May 2021. We also estimated effective and instantaneous reproduction numbers at national and provincial levels using established methods and evaluated the mobility trends using Google’s mobility data. Our forecast estimates indicated a declining trend of COVID-19 cases in Nepal as of June 2021. Sub-epidemic and Richards models provided reasonable short-term projections of COVID-19 cases based on standard performance metrics. There was a linear pattern in the trajectory of COVID-19 incidence during the first wave (deceleration of growth parameter (p) = 0.41–0.43, reproduction number (

R_{t}

) at 1.1 (95% CI: 1.1, 1.2)), and a sub-exponential growth pattern in the second wave (p = 0.61 (95% CI: 0.58, 0.64)) and

R_{t}

at 1.3 (95% CI: 1.3, 1.3)). Across provinces,

R_{t}

ranged from 1.2 to 1.5 during the early growth phase of the second wave. The instantaneous

R_{t}

fluctuated around 1.0 since January 2021 indicating well sustained transmission. The peak in mobility across different areas coincided with an increasing incidence trend of COVID-19. In conclusion, we found that the sub-epidemic and Richards models yielded reasonable short-terms projections of the COVID-19 trajectory in Nepal, which are useful for healthcare utilization planning. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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12 pages, 2100 KiB

Open AccessArticle

Epidemiological Analysis of COVID-19 Cases in Native Amazonian Communities from Peru

by Cecilia Pajuelo-Reyes, Hugo J. Valencia, Carla C. Montenegro, Eduardo Quezada, Lizandro Gonzales, Norma Cruz, Carlos Canelo, Carla Ordinola, Jorge L. Maicelo Quintana, Juan R. Tejedo, Rafael Tapia-Limonchi and Stella M. Chenet

Epidemiologia 2021, 2(4), 490-501; https://doi.org/10.3390/epidemiologia2040034 - 9 Oct 2021

Cited by 4 | Viewed by 4515

Abstract

Despite early control measures, SARS-CoV-2 reached all regions of Peru during the first wave of the pandemic, including native communities of the Peruvian Amazon. Here, we aimed to describe the epidemiological situation of COVID-19 in the Amazonas region of Peru using an open [...] Read more.

Despite early control measures, SARS-CoV-2 reached all regions of Peru during the first wave of the pandemic, including native communities of the Peruvian Amazon. Here, we aimed to describe the epidemiological situation of COVID-19 in the Amazonas region of Peru using an open database of 11,124 COVID-19 cases reported from 19 March to 29 July 2020, including 3278 cases from native communities. A high-incidence area in northern Amazonas (Condorcanqui) reported a cumulative incidence of 63.84/1000 inhabitants with a much lower death rate (0.95%) than the national average. Our results showed at least eight significant factors for mortality, and the Native Amazonian ethnicity as a protective factor. Molecular confirmatory tests are necessary to better explain the high incidence of antibody response reported in these communities. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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19 pages, 828 KiB

Open AccessArticle

Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model with Varying Mitigation Measures and Transmission Rate

by K. D. Olumoyin, A. Q. M. Khaliq and K. M. Furati

Epidemiologia 2021, 2(4), 471-489; https://doi.org/10.3390/epidemiologia2040033 - 24 Sep 2021

Cited by 16 | Viewed by 3877

Abstract

Epidemiological models with constant parameters may not capture satisfactory infection patterns in the presence of pharmaceutical and non-pharmaceutical mitigation measures during a pandemic, since infectiousness is a function of time. In this paper, an Epidemiology-Informed Neural Network algorithm is introduced to learn the [...] Read more.

Epidemiological models with constant parameters may not capture satisfactory infection patterns in the presence of pharmaceutical and non-pharmaceutical mitigation measures during a pandemic, since infectiousness is a function of time. In this paper, an Epidemiology-Informed Neural Network algorithm is introduced to learn the time-varying transmission rate for the COVID-19 pandemic in the presence of various mitigation scenarios. There are asymptomatic infectives, mostly unreported, and the proposed algorithm learns the proportion of the total infective individuals that are asymptomatic infectives. Using cumulative and daily reported cases of the symptomatic infectives, we simulate the impact of non-pharmaceutical mitigation measures such as early detection of infectives, contact tracing, and social distancing on the basic reproduction number. We demonstrate the effectiveness of vaccination on the transmission of COVID-19. The accuracy of the proposed algorithm is demonstrated using error metrics in the data-driven simulation for COVID-19 data of Italy, South Korea, the United Kingdom, and the United States. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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11 pages, 1867 KiB

Open AccessArticle

The Role of Mobility and Sanitary Measures on the Delay of Community Transmission of COVID-19 in Costa Rica

by Luis A. Barboza, Paola Vásquez, Gustavo Mery, Fabio Sanchez, Yury E. García, Juan G. Calvo, Tania Rivas, María Dolores Pérez and Daniel Salas

Epidemiologia 2021, 2(3), 294-304; https://doi.org/10.3390/epidemiologia2030022 - 21 Jul 2021

Cited by 4 | Viewed by 3970

Abstract

The aim of this paper is to infer the effects that change on human mobility had on the transmission dynamics during the first four months of the SARS-CoV-2 pandemic in Costa Rica, which could have played a role in delaying community transmission in [...] Read more.

The aim of this paper is to infer the effects that change on human mobility had on the transmission dynamics during the first four months of the SARS-CoV-2 pandemic in Costa Rica, which could have played a role in delaying community transmission in the country. First, by using parametric and non-parametric change-point detection techniques, we were able to identify two different periods when the trend of daily new cases significantly changed. Second, we explored the association of these changes with data on population mobility. This also allowed us to estimate the lag between changes in human mobility and rates of daily new cases. The information was then used to establish an association between changes in population mobility and the sanitary measures adopted during the study period. Results showed that during the initial two months of the pandemic in Costa Rica, the implementation of sanitary measures and their impact on reducing human mobility translated to a mean reduction of 54% in the number of daily cases from the projected number, delaying community transmission. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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9 pages, 1092 KiB

Open AccessArticle

Epidemiology of COVID-19 in the State of Sergipe/Brazil and Its Relationship with Social Indicators

by Larissa M. Fonseca, Derijuli S. de Sousa, Juliana C. Cardoso, Patricia Severino, Amanda Cano, Eliana B. Souto, Sônia O. Lima, Cristiane C. C. de Oliveira and Francisco P. Reis

Epidemiologia 2021, 2(3), 262-270; https://doi.org/10.3390/epidemiologia2030020 - 14 Jul 2021

Cited by 2 | Viewed by 2544

Abstract

A pandemic is capable of generating a great impact, not only from the point of view of health, but also socioeconomically. In March 2020, the World Health Organization (WHO) declared that a new pandemic situation had arisen, due to the SARS-CoV-2 virus, whose [...] Read more.

A pandemic is capable of generating a great impact, not only from the point of view of health, but also socioeconomically. In March 2020, the World Health Organization (WHO) declared that a new pandemic situation had arisen, due to the SARS-CoV-2 virus, whose probable origin was zoonotic. The largest number of cases of this disease is concentrated in the United States of America (USA), India, and Brazil. The mortality rate is estimated at 3.4%, but regional differences may exist, and places with a high demographic density have become true epicentres and may be related to higher rates of transmission. In addition to the above, lower human development indexes (HDI) can be related to worse outcomes, especially in the North and Northeast regions of Brazil since they are the least developed places. The Northeast region is the second-most-affected place in the number of COVID-19 cases in Brazil. An analytical observational study of an ecological type was carried out from April to October 2020 to assess the epidemiological situation of COVID-19 in the state of Sergipe and specifically to analyse the incidence of cases and deaths resulting from COVID-19 in the different health regions of the state of Sergipe, in relation to the values of the HDI and demographic density. During the study period, 84,325 cases of COVID-19 were identified, in which 2205 resulted in death. In most of the regions studied, there was a positive association between the number of cases and deaths and the greater the demographic density, but there was no increase in the risk of becoming ill, nor of dying the lower the HDI. Large and crowded cities are places of greatest vulnerability to illness, due to their greater capacity of transmitting the virus; however, further studies are needed to identify other factors that are decisive in the outcomes of this new disease. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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16 pages, 325 KiB

Open AccessArticle

A Cross-Sectional Examination of the Mental Wellbeing, Coping and Quality of Working Life in Health and Social Care Workers in the UK at Two Time Points of the COVID-19 Pandemic

by Paula McFadden, Ruth D. Neill, John Moriarty, Patricia Gillen, John Mallett, Jill Manthorpe, Denise Currie, Heike Schroder, Jermaine Ravalier, Patricia Nicholl, Daniel McFadden and Jana Ross

Epidemiologia 2021, 2(3), 227-242; https://doi.org/10.3390/epidemiologia2030017 - 22 Jun 2021

Cited by 17 | Viewed by 6069

Abstract

As the COVID-19 pandemic continues to evolve around the world, it is important to examine its effect on societies and individuals, including health and social care (HSC) professionals. The aim of this study was to compare cross-sectional data collected from HSC staff in [...] Read more.

As the COVID-19 pandemic continues to evolve around the world, it is important to examine its effect on societies and individuals, including health and social care (HSC) professionals. The aim of this study was to compare cross-sectional data collected from HSC staff in the UK at two time points during the COVID-19 pandemic: Phase 1 (May–July 2020) and Phase 2 (November 2020–January 2021). The HSC staff surveyed consisted of nurses, midwives, allied health professionals, social care workers and social workers from across the UK (England, Wales, Scotland, Northern Ireland). Multiple regressions were used to examine the effects of different coping strategies and demographic and work-related variables on participants’ wellbeing and quality of working life to see how and if the predictors changed over time. An additional multiple regression was used to directly examine the effects of time (Phase 1 vs. Phase 2) on the outcome variables. Findings suggested that both wellbeing and quality of working life deteriorated from Phase 1 to Phase 2. The results have the potential to inform interventions for HSC staff during future waves of the COVID-19 pandemic, other infectious outbreaks or even other circumstances putting long-term pressures on HSC systems. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

20 pages, 1431 KiB

Open AccessFeature PaperArticle

Mask-Ematics: Modeling the Effects of Masks in COVID-19 Transmission in High-Risk Environments

by Anthony Morciglio, Bin Zhang, Gerardo Chowell, James M. Hyman and Yi Jiang

Epidemiologia 2021, 2(2), 207-226; https://doi.org/10.3390/epidemiologia2020016 - 31 May 2021

Cited by 4 | Viewed by 4420

Abstract

The COVID-19 pandemic has placed an unprecedented burden on public health and strained the worldwide economy. The rapid spread of COVID-19 has been predominantly driven by aerosol transmission, and scientific research supports the use of face masks to reduce transmission. However, a systematic [...] Read more.

The COVID-19 pandemic has placed an unprecedented burden on public health and strained the worldwide economy. The rapid spread of COVID-19 has been predominantly driven by aerosol transmission, and scientific research supports the use of face masks to reduce transmission. However, a systematic and quantitative understanding of how face masks reduce disease transmission is still lacking. We used epidemic data from the Diamond Princess cruise ship to calibrate a transmission model in a high-risk setting and derive the reproductive number for the model. We explain how the terms in the reproductive number reflect the contributions of the different infectious states to the spread of the infection. We used that model to compare the infection spread within a homogeneously mixed population for different types of masks, the timing of mask policy, and compliance of wearing masks. Our results suggest substantial reductions in epidemic size and mortality rate provided by at least 75% of people wearing masks (robust for different mask types). We also evaluated the timing of the mask implementation. We illustrate how ample compliance with moderate-quality masks at the start of an epidemic attained similar mortality reductions to less compliance and the use of high-quality masks after the epidemic took off. We observed that a critical mass of 84% of the population wearing masks can completely stop the spread of the disease. These results highlight the significance of a large fraction of the population needing to wear face masks to effectively reduce the spread of the epidemic. The simulations show that early implementation of mask policy using moderate-quality masks is more effective than a later implementation with high-quality masks. These findings may inform public health mask-use policies for an infectious respiratory disease outbreak (such as one of COVID-19) in high-risk settings. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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19 pages, 4524 KiB

Open AccessArticle

Spatially Refined Time-Varying Reproduction Numbers of COVID-19 by Health District in Georgia, USA, March–December 2020

by Chigozie A. Ogwara, Arshpreet Kaur Mallhi, Xinyi Hua, Kamalich Muniz-Rodriguez, Jessica S. Schwind, Xiaolu Zhou, Jeffery A. Jones, Joanne Chopak-Foss, Gerardo Chowell and Isaac Chun-Hai Fung

Epidemiologia 2021, 2(2), 179-197; https://doi.org/10.3390/epidemiologia2020014 - 28 May 2021

Cited by 7 | Viewed by 3670

Abstract

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, R_t of SARS-CoV-2 in Georgia and its 18 public health [...] Read more.

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, R_t of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package ‘EpiEstim’ to the time series of historical daily incidence of confirmed cases, 2 March–15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log₁₀-transformed per capita cumulative case count and log₁₀-transformed population size. We observe R_t fluctuations as state and countywide policies are implemented. Policy changes are associated with increases or decreases at different time points. R_t increases, following the reopening of schools for in-person instruction in August. Evidence suggests that counties with lower population size had a higher per capita cumulative case count on June 15 (slope = −0.10, p = 0.04) and October 15 (slope = −0.05, p = 0.03), but not on August 15 (slope = −0.04, p = 0.09), nor December 15 (slope = −0.02, p = 0.41). We found extensive community transmission of SARS-CoV-2 across all 18 health districts in Georgia with median 7-day-sliding window R_t estimates between 1 and 1.4 after March 2020. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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22 pages, 500 KiB

Open AccessArticle

Analysis of Key Factors of a SARS-CoV-2 Vaccination Program: A Mathematical Modeling Approach

by David Martínez-Rodríguez, Gilberto Gonzalez-Parra and Rafael-J. Villanueva

Epidemiologia 2021, 2(2), 140-161; https://doi.org/10.3390/epidemiologia2020012 - 1 Apr 2021

Cited by 22 | Viewed by 5710

Abstract

The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020. Currently, there are only a few approved vaccines, each with different efficacies and mechanisms of action. Moreover, vaccination programs in different regions may vary due to differences [...] Read more.

The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020. Currently, there are only a few approved vaccines, each with different efficacies and mechanisms of action. Moreover, vaccination programs in different regions may vary due to differences in implementation, for instance, simply the availability of the vaccine. In this article, we study the impact of the pace of vaccination and the intrinsic efficacy of the vaccine on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. Then we study different potential scenarios regarding the burden of the COVID-19 pandemic in the near future. We construct a compartmental mathematical model and use computational methodologies to study these different scenarios. Thus, we are able to identify some key factors to reach the aims of the vaccination programs. We use some metrics related to the outcomes of the COVID-19 pandemic in order to assess the impact of the efficacy of the vaccine and the pace of the vaccine inoculation. We found that both factors have a high impact on the outcomes. However, the rate of vaccine administration has a higher impact in reducing the burden of the COVID-19 pandemic. This result shows that health institutions need to focus on increasing the vaccine inoculation pace and create awareness in the population about the importance of COVID-19 vaccines. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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19 pages, 6624 KiB

Open AccessArticle

Assessing Early Heterogeneity in Doubling Times of the COVID-19 Epidemic across Prefectures in Mainland China, January–February, 2020

by Isaac Chun-Hai Fung, Xiaolu Zhou, Chi-Ngai Cheung, Sylvia K. Ofori, Kamalich Muniz-Rodriguez, Chi-Hin Cheung, Po-Ying Lai, Manyun Liu and Gerardo Chowell

Epidemiologia 2021, 2(1), 95-113; https://doi.org/10.3390/epidemiologia2010009 - 11 Mar 2021

Cited by 6 | Viewed by 2741

Abstract

To describe the geographical heterogeneity of COVID-19 across prefectures in mainland China, we estimated doubling times from daily time series of the cumulative case count between 24 January and 24 February 2020. We analyzed the prefecture-level COVID-19 case burden using linear regression models [...] Read more.

To describe the geographical heterogeneity of COVID-19 across prefectures in mainland China, we estimated doubling times from daily time series of the cumulative case count between 24 January and 24 February 2020. We analyzed the prefecture-level COVID-19 case burden using linear regression models and used the local Moran’s I to test for spatial autocorrelation and clustering. Four hundred prefectures (~98% population) had at least one COVID-19 case and 39 prefectures had zero cases by 24 February 2020. Excluding Wuhan and those prefectures where there was only one case or none, 76 (17.3% of 439) prefectures had an arithmetic mean of the epidemic doubling time <2 d. Low-population prefectures had a higher per capita cumulative incidence than high-population prefectures during the study period. An increase in population size was associated with a very small reduction in the mean doubling time (−0.012, 95% CI, −0.017, −0.006) where the cumulative case count doubled ≥3 times. Spatial analysis revealed high case count clusters in Hubei and Heilongjiang and fast epidemic growth in several metropolitan areas by mid-February 2020. Prefectures in Hubei and neighboring provinces and several metropolitan areas in coastal and northeastern China experienced rapid growth with cumulative case count doubling multiple times with a small mean doubling time. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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9 pages, 313 KiB

Open AccessArticle

The Effect of Face Mask Use on COVID-19 Models

by Fan Bai and Fred Brauer

Epidemiologia 2021, 2(1), 75-83; https://doi.org/10.3390/epidemiologia2010007 - 26 Feb 2021

Cited by 9 | Viewed by 3281

Abstract

We begin with a simple model for the COVID-19 epidemic and add face mask usages and testing and quarantine of infectives. We estimate the effect on the reproduction number and discuss the question of whether the epidemic can be controlled by increased use [...] Read more.

We begin with a simple model for the COVID-19 epidemic and add face mask usages and testing and quarantine of infectives. We estimate the effect on the reproduction number and discuss the question of whether the epidemic can be controlled by increased use of face masks. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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13 pages, 658 KiB

Open AccessArticle

COVID-19 Epidemic in Bangladesh among Rural and Urban Residents: An Online Cross-Sectional Survey of Knowledge, Attitudes, and Practices

by Md. Siddikur Rahman, Ajlina Karamehic-Muratovic, Miftahuzzannat Amrin, Arman Hossain Chowdhury, Md. Selim Mondol, Ubydul Haque and Parveen Ali

Epidemiologia 2021, 2(1), 1-13; https://doi.org/10.3390/epidemiologia2010001 - 22 Dec 2020

Cited by 23 | Viewed by 6346

Abstract

As other nations around the world, Bangladesh is facing enormous challenges with the novel coronavirus (COVID-19) epidemic. To design a prevention and control strategy for this new infectious disease, it is essential to first understand people’s knowledge, attitudes, and practices (KAP) regarding COVID-19. [...] Read more.

As other nations around the world, Bangladesh is facing enormous challenges with the novel coronavirus (COVID-19) epidemic. To design a prevention and control strategy for this new infectious disease, it is essential to first understand people’s knowledge, attitudes, and practices (KAP) regarding COVID-19. This study sought to determine KAP among rural and urban residents as well as predictors of preventive practices associated with COVID-19 in Bangladesh. A social media-based (Facebook) cross-sectional survey was conducted to explore these variables among Bangladeshi adults. Of 1520 respondents who completed the questionnaire, low level of good or sufficient knowledge of COVID-19 (70.8%) and practices associated with COVID-19 (73.8%) were found. Despite the low level of knowledge and practices, respondents’ attitude (78.9%) towards COVID-19 was relatively high. Results suggest that compared to urban, rural residents are at a particularly high risk of COVID-19 because they were found to have significantly lower knowledge (p = 0.001) and practice levels (p = 0.002) than were urban residents. Multivariable logistic regression analysis identified gender, education, knowledge of COVID-19 transmission, signs and symptoms, and sources of information as factors significantly associated with preventive practices against COVID-19. Further attention and effort should be directed toward increasing both knowledge and practices targeting the general population in Bangladesh, particularly the rural and less educated residents. Findings from this study provide baseline data that can be used to promote integrated awareness of and effective health education programs about COVID-19 prevention and control strategies in Bangladesh, and similar COVID-19 endemic countries. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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11 pages, 1072 KiB

Open AccessFeature PaperArticle

Initial Inoculum and the Severity of COVID-19: A Mathematical Modeling Study of the Dose-Response of SARS-CoV-2 Infections

by Baylor Fain and Hana M. Dobrovolny

Epidemiologia 2020, 1(1), 5-15; https://doi.org/10.3390/epidemiologia1010003 - 21 Oct 2020

Cited by 19 | Viewed by 6750

Abstract

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) causes a variety of responses in those who contract the virus, ranging from asymptomatic infections to acute respiratory failure and death. While there are likely multiple mechanisms triggering severe disease, one potential cause of severe disease [...] Read more.

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) causes a variety of responses in those who contract the virus, ranging from asymptomatic infections to acute respiratory failure and death. While there are likely multiple mechanisms triggering severe disease, one potential cause of severe disease is the size of the initial inoculum. For other respiratory diseases, larger initial doses lead to more severe outcomes. We investigate whether there is a similar link for SARS-CoV-2 infections using the combination of an agent-based model (ABM) and a partial differential equation model (PDM). We use the model to examine the viral time course for different sizes of initial inocula, generating dose-response curves for peak viral load, time of viral peak, viral growth rate, infection duration, and area under the viral titer curve. We find that large initial inocula lead to short infections, but with higher viral titer peaks; and that smaller initial inocula lower the viral titer peak, but make the infection last longer. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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Review

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13 pages, 6650 KiB

Open AccessReview

The COVID-19 Pandemic in Brazil: Some Aspects and Tools

by Pedro Rafael D. Marinho, Gauss M. Cordeiro, Hemilio Fernandes C. Coelho and Poliana C. Cabral

Epidemiologia 2021, 2(3), 243-255; https://doi.org/10.3390/epidemiologia2030018 - 23 Jun 2021

Cited by 4 | Viewed by 3706

Abstract

The article presents some aspects related to the COVID-19 pandemic in Brazil including public health, challenges facing healthcare workers and adverse impacts on the country’s economy. Its main contribution is the availability of two web applications for online monitoring of the evolution of [...] Read more.

The article presents some aspects related to the COVID-19 pandemic in Brazil including public health, challenges facing healthcare workers and adverse impacts on the country’s economy. Its main contribution is the availability of two web applications for online monitoring of the evolution of the pandemic in Brazil and South America. The applications provide the possibility to download data in different formats, view interactive maps and graphs of the cumulative confirmed cases, deaths and lethality rates, in addition to presenting plots of moving averages for states and municipalities. The predictions about new cases and new deaths caused by COVID-19, in states and regions of Brazil, are also reported using GAMLSS models. The forecasts can be easily used by public managers for effective decision-making. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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9 pages, 1318 KiB

Open AccessReview

Imported COVID-19 Cases from Iran: A Rapid Review

by Tasnim Abdalla, Khaled Aboujabal, Menatella Abdelnaby, Rim Bashir, Yara Wanas and Elmoubasher Farag

Epidemiologia 2021, 2(2), 198-206; https://doi.org/10.3390/epidemiologia2020015 - 29 May 2021

Viewed by 3778

Abstract

This review aims to map the spread of the virus from Iran to the Middle East and the rest of the world and to help better understand the key trends that occurred during COVID-19 from this epidemic center. We performed a literature review [...] Read more.

This review aims to map the spread of the virus from Iran to the Middle East and the rest of the world and to help better understand the key trends that occurred during COVID-19 from this epidemic center. We performed a literature review which was undertaken from 16 June to 22 November 2020. We reviewed the available evidence on imported cases from Iran, in the electronic databases PubMed and Google Scholar, as well as gray literature. It is shown that 125 cases were imported from Iran, out of which most of the imported cases were asymptomatic, and PCR testing was the most common method of detection. It was also found that more than half of the imported cases were not quarantined or isolated at home. The review revealed that many countries, especially the Middle East had imported cases from Iran. The big gap between the date of arrival at the airport and the date of diagnosis emphasizes the importance of early detection and quarantine measures, to stop the spread of the virus. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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16 pages, 992 KiB

Open AccessReview

How the Heart Was Involved in COVID-19 during the First Pandemic Phase: A Review

by Andrea Canalella, Ermanno Vitale, Francesca Vella, Paola Senia, Emanuele Cannizzaro, Caterina Ledda and Venerando Rapisarda

Epidemiologia 2021, 2(1), 124-139; https://doi.org/10.3390/epidemiologia2010011 - 22 Mar 2021

Cited by 2 | Viewed by 3221

Abstract

Coronavirus disease (COVID-19) was first observed in Wuhan, Hubei Province (China) in December 2019, resulting in an acute respiratory syndrome. Only later was COVID-19 considered a public health emergency of international concern and, on 11 March 2020, the WHO classified it as pandemic. [...] Read more.

Coronavirus disease (COVID-19) was first observed in Wuhan, Hubei Province (China) in December 2019, resulting in an acute respiratory syndrome. Only later was COVID-19 considered a public health emergency of international concern and, on 11 March 2020, the WHO classified it as pandemic. Despite being a respiratory virus, the clinical manifestations are also characterized by cardiological involvement, especially in patients suffering from previous comorbidities such as hypertension and diabetes mellitus, its complications being potentially serious or fatal. Despite the efforts made by the scientific community to identify pathophysiological mechanisms, they still remain unclear. A fundamental role is played by the angiotensin 2 converting enzyme, known for its effects at the cardiovascular level and for its involvement in COVID-19 pathogenesis. The goal of this paper was to highlight the mechanisms and knowledge related to cardiovascular involvement during the first pandemic phase, as well as to emphasize the main cardiological complications in infected patients. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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Other

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10 pages, 632 KiB

Open AccessData Descriptor

A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

by Juan M. Banda, Ramya Tekumalla, Guanyu Wang, Jingyuan Yu, Tuo Liu, Yuning Ding, Ekaterina Artemova, Elena Tutubalina and Gerardo Chowell

Epidemiologia 2021, 2(3), 315-324; https://doi.org/10.3390/epidemiologia2030024 - 5 Aug 2021

Cited by 135 | Viewed by 17816

Abstract

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic [...] Read more.

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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10 pages, 780 KiB

Open AccessBrief Report

Rapid and Convenient Quantitative Analysis of SARS-CoV-2 RNA in Serous Saliva with a Direct PCR Method

by Chikaya Deura and Kenji Nakayama

Epidemiologia 2021, 2(3), 305-314; https://doi.org/10.3390/epidemiologia2030023 - 28 Jul 2021

Cited by 2 | Viewed by 3484

Abstract

Sensitive and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), frequently performed using direct polymerase chain reaction (PCR), is essential for restricting the spread of coronavirus disease 2019 (COVID-19). However, studies evaluating accurate detection are still required. This study evaluated the [...] Read more.

Sensitive and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), frequently performed using direct polymerase chain reaction (PCR), is essential for restricting the spread of coronavirus disease 2019 (COVID-19). However, studies evaluating accurate detection are still required. This study evaluated the quantitativeness and sensitivity of the Ampdirect™ 2019-nCoV detection kit, a direct PCR method. Using saliva with or without Tris-buffered saline (TBS) dilution, linearity, and limits of the N1 and N2 regions of SARS-CoV-2 genomic RNA were assessed using EDX SARS-CoV-2 RNA standard dissolved in RNase-free water (RFW). Fluorescence intensities in non-diluted saliva were higher than those in TBS-diluted samples. Linear regression analysis of detected quantification cycle values and spiked standard RNA concentrations showed that the coefficient of determination of the N1 and N2 genes was 0.972 and 0.615 in RFW and 0.947 and 0.660 in saliva, respectively. N1- and N2-positive detection rates in saliva were 46% (6/13 tests) and 0% (0/12 tests) at one copy/reaction, respectively. These results indicate good quantitativeness and sensitivity for N1 but not for N2. Therefore, our findings reveal that the Ampdirect™ 2019-nCoV system, especially targeting the N1 gene, enables rapid and convenient quantification of SARS-CoV-2 RNA in saliva at one copy/reaction. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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Open AccessBrief Report

Masks, Gloves, and the COVID-19 Pandemic: Rapid Assessment of Public Behaviors in the United States

by Jagdish Khubchandani, Diana Saiki and Jayanthi Kandiah

Epidemiologia 2020, 1(1), 16-22; https://doi.org/10.3390/epidemiologia1010004 - 5 Nov 2020

Cited by 34 | Viewed by 6048

Abstract

The COVID-19 outbreak was declared a national emergency in the U.S. in March 2020, and in April 2020, the U.S. government authorities issued recommendations on the use of masks and gloves as protective measures. Despite such recommendations, popular media reports highlighted a lack [...] Read more.

The COVID-19 outbreak was declared a national emergency in the U.S. in March 2020, and in April 2020, the U.S. government authorities issued recommendations on the use of masks and gloves as protective measures. Despite such recommendations, popular media reports highlighted a lack of compliance. However, no systematic study has examined the use of protective strategies (e.g., wearing a mask) by the American public to prevent the spread of COVID-19 during early stages of the pandemic. The purpose of this study was to conduct a rapid national assessment of public behaviors to prevent COVID-19 spread during the early stages of the pandemic and to assess how these behaviors may have differed based on selected sociodemographic characteristics. A total of 835 adult Americans nationwide took a multi-item survey and were asked about wearing masks, gloves, and their demographic background. The majority of the study participants reported wearing a mask more often during the pandemic (76%), but the majority did not wear gloves more often during the pandemic (30%). Significant differences (p < 0.05) for wearing masks were found based on sex, age, ethnicity, marital status, living arrangements, and employment status. For gloves, significant differences were found based on sex, age, marital status, and employment. While the pandemic continues to unfold and with recent reports of a surge in cases in the U.S., public health practitioners and policymakers must emphasize COVID-19 prevention strategies for the general public and explore pragmatic options to increase compliance of protective behaviors among the general public. Full article

(This article belongs to the Special Issue Evolving COVID-19 Epidemiology and Dynamics)

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