COVID-19 is the most significant global crisis of any of our lifetimes. The numbers have been stupefying, whether of infection and mortality, the scale of public health measures, or the economic ...consequences of shutdown. Coronavirus Politics identifies key threads in the global comparative discussion that continue to shed light on COVID-19 and shape debates about what it means for scholarship in health and comparative politics. Editors Scott L. Greer, Elizabeth J. King, Elize Massard da Fonseca, and André Peralta-Santos bring together over 30 authors versed in politics and the health issues in order to understand the health policy decisions, the public health interventions, the social policy decisions, their interactions, and the reasons. The book’s coverage is global, with a wide range of key and exemplary countries, and contains a mixture of comparative, thematic, and templated country studies. All go beyond reporting and monitoring to develop explanations that draw on the authors' expertise while engaging in structured conversations across the book.
We estimated comparative primary and booster vaccine effectiveness (VE) of SARS-CoV-2 Omicron BA.5 and BA.2 lineages against infection and disease progression. During April-June 2022, we implemented ...a case-case and cohort study and classified lineages using whole-genome sequencing or spike gene target failure. For the case-case study, we estimated the adjusted odds ratios (aORs) of vaccination using a logistic regression. For the cohort study, we estimated VE against disease progression using a penalized logistic regression. We observed no reduced VE for primary (aOR 1.07 95% CI 0.93-1.23) or booster (aOR 0.96 95% CI 0.84-1.09) vaccination against BA.5 infection. Among BA.5 case-patients, booster VE against progression to hospitalization was lower than that among BA.2 case-patients (VE 77% 95% CI 49%-90% vs. VE 93% 95% CI 86%-97%). Although booster vaccination is less effective against BA.5 than against BA.2, it offers substantial protection against progression from BA.5 infection to severe disease.
Through deterministic data linkage of health registries, mRNA vaccine effectiveness (VE) against COVID-19-related hospitalisations and deaths was measured in 1,880,351 older adults. VE against ...hospitalisations was 94% (95% confidence interval (CI): 88–97) and 82% (95% CI: 72–89) for those 65–79 and ≥ 80 years old, with no evidence of waning 98 days after dose two. VE against mortality was 96% (95% CI: 92–98) and 81% (95% CI: 74–87) in these two age groups.
During the SARS-CoV-2 pandemic, governments and public health authorities collected massive amounts of data on daily confirmed positive cases and incidence rates. These data sets provide relevant ...information to develop a scientific understanding of the pandemic's spatiotemporal dynamics. At the same time, there is a lack of comprehensive approaches to describe and classify patterns underlying the dynamics of COVID-19 incidence across regions over time. This seriously constrains the potential benefits for public health authorities to understand spatiotemporal patterns of disease incidence that would allow for better risk communication strategies and improved assessment of mitigation policies efficacy. Within this context, we propose an exploratory statistical tool that combines functional data analysis with unsupervised learning algorithms to extract meaningful information about the main spatiotemporal patterns underlying COVID-19 incidence on mainland Portugal. We focus on the timeframe spanning from August 2020 to March 2022, considering data at the municipality level. First, we describe the temporal evolution of confirmed daily COVID-19 cases by municipality as a function of time, and outline the main temporal patterns of variability using a functional principal component analysis. Then, municipalities are classified according to their spatiotemporal similarities through hierarchical clustering adapted to spatially correlated functional data. Our findings reveal disparities in disease dynamics between northern and coastal municipalities versus those in the southern and hinterland. We also distinguish effects occurring during the 2020-2021 period from those in the 2021-2022 autumn-winter seasons. The results provide proof-of-concept that the proposed approach can be used to detect the main spatiotemporal patterns of disease incidence. The novel approach expands and enhances existing exploratory tools for spatiotemporal analysis of public health data.
We developed a case-case study to compare mRNA vaccine effectiveness against Delta versus Alpha coronavirus variants. We used data on 2,097 case-patients with PCR-positive severe acute respiratory ...syndrome coronavirus 2 infections reported in Portugal during May-July 2021. We estimated the odds of vaccine breakthrough infection in Delta-infected versus Alpha-infected patients by using conditional logistic regression adjusted for age group and sex and matched by the week of diagnosis. We compared reverse-transcription PCR cycle threshold values by vaccination status and variant as an indirect measure of viral load. We found significantly higher odds of vaccine breakthrough infection in Delta-infected patients than in Alpha-infected patients (odds ratio 1.96 95% CI 1.22-3.14), suggesting lower effectiveness of the mRNA vaccines in preventing infection with the Delta variant. We estimated lower mean cycle threshold values for the Delta cases (mean difference -2.10 95% CI -2.74 to -1.47), suggesting higher infectiousness than the Alpha variant.
The European Union (EU) Directive on Patients' Rights in Cross-border Healthcare clarified the entitlements to medical care in other EU Member states. However, little is known about whether EU ...citizens have been travelling or are willing to travel to receive care. This study aimed to measure the determinants of cross-border patient mobility and willingness to travel to receive medical care in the EU, before and after the adoption of the Directive.
We used individual data from the Eurobarometer 210 (2007) and 425 (2014). In the 2 years, 53 439 EU citizens were randomly selected. We performed a logistic regression on the cross-border patient mobility and willingness to travel to other EU countries to use healthcare services as a function of the year (2007 or 2014), adjusting for age, gender, education and country size.
In 2007, 3.3% of citizens reported cross-border mobility and 4.6% in 2014. The odds of cross-border patients' mobility were 11% higher in 2014, compared with 2007 odds ratio (OR) 1.11, 95% confidence interval (CI) 1.02-1.21. Also, mobility was 19% higher in males (OR 1.19, 95% CI 1.08-1.30) and 20% higher amongst the more educated (OR 1.20, 95% CI 1.09-1.31). However, the odds decreased 11% per decade of age (OR 0.89 per decade, 95% CI 0.85-0.93) and country size. In 2014, the willingness to travel decreased by 20% compared with 2007.
Cross-border patient mobility is more likely amongst the younger, the more educated and those from smaller countries. The directive does not seem to have promoted mobility at a large scale among the neediest citizens.
Self-Organizing Maps (SOM) are an unsupervised learning clustering and dimensionality reduction algorithm capable of mapping an initial complex high-dimensional data set into a low-dimensional ...domain, such as a two-dimensional grid of neurons. In the reduced space, the original complex patterns and their interactions can be better visualized, interpreted and understood.
We use SOM to simultaneously couple the spatial and temporal domains of the COVID-19 evolution in the 278 municipalities of mainland Portugal during the first year of the pandemic. Temporal 14-days cumulative incidence time series along with socio-economic and demographic indicators per municipality were analyzed with SOM to identify regions of the country with similar behavior and infer the possible common origins of the incidence evolution.
The results show how neighbor municipalities tend to share a similar behavior of the disease, revealing the strong spatiotemporal relationship of the COVID-19 spreading beyond the administrative borders of each municipality. Additionally, we demonstrate how local socio-economic and demographic characteristics evolved as determinants of COVID-19 transmission, during the 1st wave school density per municipality was more relevant, where during 2nd wave jobs in the secondary sector and the deprivation score were more relevant.
The results show that SOM can be an effective tool to analysing the spatiotemporal behavior of COVID-19 and synthetize the history of the disease in mainland Portugal during the period in analysis. While SOM have been applied to diverse scientific fields, the application of SOM to study the spatiotemporal evolution of COVID-19 is still limited. This work illustrates how SOM can be used to describe the spatiotemporal behavior of epidemic events. While the example shown herein uses 14-days cumulative incidence curves, the same analysis can be performed using other relevant data such as mortality data, vaccination rates or even infection rates of other disease of infectious nature.
We show that the SARS-CoV-2 B.1.1.7 lineage is highly disseminated in Portugal, with the odds of B.1.1.7 proportion increasing at an estimated 89% (95% confidence interval: 83-95%) per week until ...week 3 2021. RT-PCR spike gene target late detection (SGTL) can constitute a useful surrogate to track B.1.1.7 spread, besides the spike gene target failure (SGTF) proxy. SGTL/SGTF samples were associated with statistically significant higher viral loads, but not with substantial shift in age distribution compared to non-SGTF/SGTL cases.
Objectives
In June 2015, Partners in Health (PIH) and the Liberian Ministry of Health began a community health worker (CHW) programme containing food support, reimbursement of transport and social ...assistance to address gaps in tuberculosis (TB) treatment exacerbated by the 2014‐2015 Ebola virus disease (EVD) epidemic. The purpose of this article was to analyse the performance of routine clinical TB care and the effects of this CHW programme.
Methods
Retrospective cohort study utilising data from TB patient registers at a census of all health facilities treating TB in the south‐east region of Liberia from January 2015 – April 2017. Competing risks Cox regression analyses were used to generate subhazard ratios (sHR) analysing factors associated with rates of TB cure (smear negative), treatment completion (no smear), lost to follow‐up (LTFU) and death.
Results
LTFU rates decreased 76% pre‐ vs. post‐CHW intervention, from 14.6% in pre‐intervention to 3.4% post‐intervention (P < 0.001). Although the post‐intervention had better cure rates (sHR 1.07, CI 0.58‐1.9), treatment completion (sHR 1.53, CI 1.00 2.39) and lower death rates (sHR 0.64, CI 0.34‐1.2), statistical significance was not reached. Younger patients had significantly lower death and cure rates, while older patients had higher LTFU and cure rates. Overall, 31% of patients were cured, 44% completed treatment without a confirmatory smear, 5% were LTFU, 9% died, 0.5% failed treatment, and 10% transferred out.
Conclusions
In challenging environments, LTFU can be reduced by CHW accompaniment and socio‐economic assistance to patients with TB. Approaches are needed to improve cure verification in young patients and reduce mortality.
Objectifs
En juin 2015, Partners in Health (PIH) et le ministère libérien de la Santé ont lancé un programme d'agents de santé communautaire (ASC), de soutien alimentaire, de remboursement des frais de transport et d'assistance sociale pour combler les lacunes dans le traitement de la tuberculose exacerbée par l’épidémie de 2014–2015 de la maladie de virus Ebola (EVD). Le but de cet article est d'analyser la performance des soins cliniques TB de routine et les effets de ce programme ASC.
Méthodes
Etude de cohorte rétrospective utilisant les données des registres des patients TB lors du recensement de tous les établissements de santé traitant la TB dans le sud‐est du Liberia de janvier 2015 à avril 2017. Des analyses de régression de Cox pour les risques ont été utilisées pour générer des ratios de sous risques (sHR) analysant des facteurs associés avec les taux de guérison de la TB (frottis négatif), d'achèvement du traitement (pas de frottis), de pertes de suivi et de décès.
Résultats
Les taux de pertes de suivi ont diminué de 76% avant l'intervention ASC par rapport à après, allant de 14,6% en pré‐intervention à 3,4% après l'intervention (P < 0,001). Bien que les taux de guérison (sHR = 1,07; IC: 0,58–1,9) et d'achèvement du traitement (sHR = 1,53; IC: 1,00–2,39) aient été meilleurs et les taux de mortalité inférieurs (sHR = 0,64; IC: 0,34–1,2) après l'intervention, la signification statistique n'a pas été atteinte. Les patients plus jeunes présentaient des taux de décès et de guérison significativement plus faibles, tandis que les patients plus âgés présentaient des taux plus élevés de pertes de suivi et de guérison. Dans l'ensemble, 31% des patients ont été guéris, 44% ont terminé le traitement sans frottis de confirmation, 5% étaient perdus de suivi, 9% sont décédés, 0,5% ont eu un échec et 10% ont été transférés.
Conclusions
Dans les environnements difficiles, la perte de suivi peut être réduite par l'accompagnement des ASC et l'assistance socioéconomique aux patients TB. Des approches sont nécessaires pour améliorer la vérification de la guérison chez les jeunes patients et réduire la mortalité.
The ability to identify and predict outbreaks during epidemic and pandemic events is critical to the development and implementation of effective mitigation measures by the relevant health and ...political authorities. However, the spatiotemporal prediction of such diseases is not straightforward due to the highly non-linear behaviour of its evolution in both space and time. The methodology proposed herein is the basis of an early warning system to predict short-term anomalous values (i.e., high and low values) of the incidence of COVID-19 at the municipality level for mainland Portugal. The proposed modelling tool combines stochastic sequential simulation and machine learning, namely symbolic regression, to model the spatiotemporal evolution of the disease. The machine learning component is used to model the 14-day incidence rate curves of COVID-19, as provided by the Portuguese Directorate-General for Health, while the geostatistical simulation component models the spatial distribution of these predictions, for a simulation grid comprising the metropolitan area of Lisbon, following a pre-defined spatial continuity pattern. The method is illustrated for a period of 5 months during 2021, and considering the entire set of 19 municipalities belonging to the metropolitan area of Lisbon, Portugal. The results show the ability of the early warning system to predict and detect anomalous high and low incidence rate values for different periods of the pandemic event during this period.
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