Latest articles in this journal
Epidemiologia, Volume 2, pp 305-314; doi:10.3390/epidemiologia2030023
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.
Epidemiologia, Volume 2, pp 294-304; doi:10.3390/epidemiologia2030022
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.
Epidemiologia, Volume 2, pp 271-293; doi:10.3390/epidemiologia2030021
The first round of vaccination against coronavirus disease 2019 (COVID-19) began in early December of 2020 in a few countries. There are several vaccines, and each has a different efficacy and mechanism of action. Several countries, for example, the United Kingdom and the USA, have been able to develop consistent vaccination programs where a great percentage of the population has been vaccinated (May 2021). However, in other countries, a low percentage of the population has been vaccinated due to constraints related to vaccine supply and distribution capacity. Countries such as the USA and the UK have implemented different vaccination strategies, and some scholars have been debating the optimal strategy for vaccine campaigns. This problem is complex due to the great number of variables that affect the relevant outcomes. In this article, we study the impact of different vaccination regimens on main health outcomes such as deaths, hospitalizations, and the number of infected. We develop a mathematical model of COVID-19 transmission to focus on this important health policy issue. Thus, we are able to identify the optimal strategy regarding vaccination campaigns. We find that for vaccines with high efficacy (>70%) after the first dose, the optimal strategy is to delay inoculation with the second dose. On the other hand, for a low first dose vaccine efficacy, it is better to use the standard vaccination regimen of 4 weeks between doses. Thus, under the delayed second dose option, a campaign focus on generating a certain immunity in as great a number of people as fast as possible is preferable to having an almost perfect immunity in fewer people first. Therefore, based on these results, we suggest that the UK implemented a better vaccination campaign than that in the USA with regard to time between doses. The results presented here provide scientific guidelines for other countries where vaccination campaigns are just starting, or the percentage of vaccinated people is small.
Epidemiologia, Volume 2, pp 262-270; doi:10.3390/epidemiologia2030020
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.
Epidemiologia, Volume 2, pp 256-261; doi:10.3390/epidemiologia2030019
Studies from around the globe have found that urbanicity is associated with greater risk for certain psychiatric disorders, though the association has been less evident in the United States. We analyzed data collected in 2019 from the RAND American Life Panel (n = 2554), which were representative of the general adult population of the United States. Using multivariable logistic regression, we examined the associations between environment of birthplace (large urban, small urban, suburban, rural) and psychiatric disorders, adjusting for sociodemographic characteristics. We found that being born in a large urban area was associated with greater odds of having any psychiatric disorder when compared with being born in a rural area. However, when looking at specific disorders, we found that being born in a large urban area was only significantly associated greater odds of anxiety disorder and post-traumatic stress disorder (PTSD), but was not associated with bipolar disorder, major depressive disorder, attention deficit/hyperactivity disorder, or alcohol/substance use disorder. Being born in a small urban area was marginally associated with anxiety disorder. Future studies should examine why urban birthplace has only been associated with anxiety disorders and PTSD in the United States, and why urbanicity is associated with mood disorders in other parts of the world but not in the United States.
Epidemiologia, Volume 2, pp 243-255; doi:10.3390/epidemiologia2030018
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.
Epidemiologia, Volume 2, pp 227-242; doi:10.3390/epidemiologia2030017
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.
Epidemiologia, Volume 2, pp 207-226; doi:10.3390/epidemiologia2020016
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.
Epidemiologia, Volume 2, pp 198-206; doi:10.3390/epidemiologia2020015
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.
Epidemiologia, Volume 2, pp 179-197; doi:10.3390/epidemiologia2020014
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, Rt 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 Rt fluctuations as state and countywide policies are implemented. Policy changes are associated with increases or decreases at different time points. Rt 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 Rt estimates between 1 and 1.4 after March 2020.