A New Model for Ranking Schools of Public Health: The Public Health Academic Ranking.

Objectives: As there is no ranking designed for schools of Public Health, the aim of this project was to create one. Methods: To design the Public Health Academic Ranking (PHAR), we used the InCites Benchmarking and Analytics™ software and the Web Of Science™ Core Collection database. We collected bibliometric data on 26 schools of Public Health from each continent, between August and September 2022. We included 11 research indicators/scores, covering four criteria (productivity, quality, accessibility for readers, international collaboration), for the period 2017-2021. For the Swiss School of Public Health (SSPH+), a network gathering faculties across different universities, a specific methodology was used, with member-specific research queries. Results: The five top schools of the PHAR were: London School of Hygiene and Tropical Medicine, Public Health Foundation of India, Harvard T.H. Chan School of Public Health, SSPH+, Johns Hopkins Bloomberg School of Public Health. Conclusion: The PHAR allows worldwide bibliometric ordering of schools of Public Health. As this is a pilot project, the results must be taken with caution. This article aims to critically discuss its methodology and future improvements.

Redefining pandemic preparedness: Multidisciplinary insights from the CERP modelling workshop in infectious diseases, workshop report.

In July 2023, the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 pandemic. This report summarizes the rich discussions that occurred during the workshop. The workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data, social media, and wastewater monitoring. Significant advancements were noted in the development of predictive models, with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease trends. The role of open collaboration between various stakeholders in modelling was stressed, advocating for the continuation of such partnerships beyond the pandemic. A major gap identified was the absence of a common international framework for data sharing, which is crucial for global pandemic preparedness. Overall, the workshop underscored the need for robust, adaptable modelling frameworks and the integration of different data sources and collaboration across sectors, as key elements in enhancing future pandemic response and preparedness.

[Scientific consensus-building to promote the link between science and public policy]. / La recherche de consensus scientifique pour promouvoir le lien entre science et politiques publiques.

Consensus, defined as the position on which most scientists specialized in a given field agree at a given time, is a key aspect in increasing the readability, credibility and, ultimately, the use of scientific knowledge in public (evidence-based health policy). This article presents several methods aiming at developing scientific consensus between experts, such as the conventional or rapid Delphi approach, the nominal group technique, the RAND-UCLA appropriateness method and the consensus development conference. These methods are used to synthesize expert judgements when uncertainties persist in the literature - each with its own specificities in terms of duration, number of steps and expert participants enlisted, as well as the ways in which they are involved.

Le consensus, défini comme la position sur laquelle la plupart des scientifiques spécialistes d'un domaine se mettent d'accord à un moment donné, est un aspect-clé pour augmenter la lisibilité, la crédibilité et in fine l'utilisation des savoirs scientifiques dans les politiques publiques (evidence-based health policy). Cet article présente plusieurs méthodes permettant le développement de consensus entre personnes expertes, telles que l'approche Delphi conventionnelle ou rapide, la technique du groupe nominal, la méthode d'adéquation RAND-UCLA et la conférence de consensus. Ces méthodes permettent la synthèse des jugements experts lorsque des incertitudes persistent dans la littérature ­ chacune avec des spécificités en termes de durée, du nombre d'étapes et de personnes expertes sollicitées, ainsi que des modalités de leur implication.

Asymptomatic dengue infection rate: A systematic literature review.

Objectives: Dengue infection is spreading worldwide. The clinical spectrum is broad and includes asymptomatic infections. This review provides an overview of the different proportions of asymptomatic infections described in epidemiological studies according to definitions, study designs, and detection methods. Methods: Medline and Embase databases were searched without restriction of date or language. Studies were included if they reported data on the incidence or prevalence of asymptomatic dengue infections. The data were summarized and classified according to the definitions of the term 'asymptomatic'. Results: A total of 74 studies were included. The mean proportion of asymptomatic infections among dengue-infected persons was 54% in 50 included studies. The prevalence of dengue infections detected in healthy persons was 0.2% in 24 included studies. The term 'asymptomatic' has been used to refer to 'clinically undetectable infection', but also to 'undiagnosed infection' or 'mild infection'. Only 8% were clinically undetectable laboratory-confirmed dengue infections. Conclusion: The proportion of asymptomatic dengue infections varied greatly. Studies proving data on clinically undetectable laboratory-confirmed dengue infections were very few, but provided consistent results of low proportions of asymptomatic infections. These data challenge the assumption that the majority of dengue cases are asymptomatic.

[Epidemic forecasting and COVID-19]. / Prévisions épidémiques et Covid-19.

Since December 2019, the COVID-19 pandemic has had a major impact on global health and the economy. Epidemiological forecasts are crucial for governmental decisions, healthcare officials, and the general public. A collaboration between the Institute of Global Health at the University of Geneva and the Swiss Data Science Center created an interactive dashboard providing forecasts for over 200 countries and territories. This dashboard has been a valuable tool for the public and authorities alike. The pandemic has highlighted the importance of international collaborations and a robust national surveillance system. Data collection systems, pathogen-agnostic models, and communication tools need to be consolidated and maintained in operation.

Depuis décembre 2019, la pandémie de Covid-19 a eu un impact majeur sur la santé et l'économie mondiales. Les prévisions épidémiques sont essentielles pour les décisions gouvernementales, les responsables de la santé et le public. Un projet entre l'Institut de santé globale de l'Université de Genève et le Swiss Data Science Center a créé un tableau de bord interactif fournissant des prévisions pour plus de 200 pays et territoires, qui fut un outil précieux pour le public et les autorités. La pandémie a souligné l'importance des collaborations internationales et d'un système de surveillance national solide. Les systèmes de collecte de données, les modèles agnostiques aux pathogènes et les outils de communication doivent être consolidés et maintenus en fonctionnement.

A community-based contact isolation strategy to reduce the spread of Ebola virus disease: an analysis of the 2018-2020 outbreak in the Democratic Republic of the Congo.

INTRODUCTION: Despite tremendous progress in the development of diagnostics, vaccines and therapeutics for Ebola virus disease (EVD), challenges remain in the implementation of holistic strategies to rapidly curtail outbreaks. We investigated the effectiveness of a community-based contact isolation strategy to limit the spread of the disease in the Democratic Republic of Congo (DRC). METHODS: We did a quasi-experimental comparison study. Eligible participants were EVD contacts registered from 12 June 2019 to 18 May 2020 in Beni and Mabalako Health Zones. Intervention group participants were isolated to specific community sites for the duration of their follow-up. Comparison group participants underwent contact tracing without isolation. The primary outcome was measured as the reproduction number (R) in the two groups. Secondary outcomes were the delay from symptom onset to isolation and case management, case fatality rate (CFR) and vaccination uptake. RESULTS: 27 324 EVD contacts were included in the study; 585 in the intervention group and 26 739 in the comparison group. The intervention group generated 32 confirmed cases (5.5%) in the first generation, while the comparison group generated 87 (0.3%). However, the 32 confirmed cases arising from the intervention contacts did not generate any additional transmission (R=0.00), whereas the 87 confirmed cases arising from the comparison group generated 99 secondary cases (R=1.14). The average delay between symptom onset and case isolation was shorter (1.3 vs 4.8 days; p<0.0001), CFR lower (12.5% vs 48.4%; p=0.0001) and postexposure vaccination uptake higher (86.0% vs 56.8%; p<0.0001) in the intervention group compared with the comparison group. A significant difference was also found between intervention and comparison groups in survival rate at the discharge of hospitalised confirmed patients (87.9% vs 47.7%, respectively; p=0.0004). CONCLUSION: The community-based contact isolation strategy used in DRC shows promise as a potentially effective approach for the rapid cessation of EVD transmission, highlighting the importance of rapidly implemented, community-oriented and trust-building control strategies.

Psychiatric consequences and issues of long COVID on patients with prior psychiatric comorbidities: a scoping review.

SARS-CoV-2 is a growing field of research and mental health in long COVID is one of its interesting domains. This scoping review aims at studying the outcomes of mental health in patients already known for psychiatric illness. This was done by researching the literature in two databases (Embase and PubMed) for articles studying mental health consequences of long COVID in patients already known for psychiatric history. Eleven studies were included. 6/11 studies found an effect of long COVID, with varying severity of outcomes studied, with either a worsening in length or severity. 4/11 did not find any correlation between worsening symptoms and psychiatric history. The methods for assessing which psychiatric symptoms to include and how to determine prior history were heterogeneous, making direct comparison sometimes difficult. The data seem to show worse effects of long COVID on mental health of patients with prior mental illness, with limitations regarding the heterogeneity of the studies' designs and focuses. It also highlights how neglected this population of patients is in the current state of research.

Genetic characterization of dengue virus serotype 1 circulating in Reunion Island, 2019-2021, and the Seychelles, 2015-2016.

BACKGROUND: An unprecedent increase in the number of cases and deaths reported from dengue virus (DENV) infection has occurred in the southwestern Indian ocean in recent years. From 2017 to mid-2021 more than 70,000 confirmed dengue cases were reported in Reunion Island, and 1967 cases were recorded in the Seychelles from 2015 to 2016. Both these outbreaks displayed similar trends, with the initial circulation of DENV-2 which was replaced by DENV-1. Here, we aim to determine the origin of the DENV-1 epidemic strains and to explore their genetic characteristics along the uninterrupted circulation, particularly in Reunion. METHODS: Nucleic acids were extracted from blood samples collected from dengue positive patients; DENV-1 was identified by RT-qPCR. Positive samples were used to infect VERO cells. Genome sequences were obtained from either blood samples or infected-cell supernatants through a combination of both Illumina or MinION technologies. RESULTS: Phylogenetic analyses of partial or whole genome sequences revealed that all DENV-1 sequences from Reunion formed a monophyletic cluster that belonged to genotype I and were closely related to one isolate from Sri Lanka (OL752439.1, 2020). Sequences from the Seychelles belonged to the same major phylogenetic branch of genotype V, but fell into two paraphyletic clusters, with greatest similarity for one cluster to 2016-2017 isolate from Bangladesh, Singapore and China, and for the other cluster to ancestral isolates from Singapore, dating back to 2012. Compared to publicly available DENV-1 genotype I sequences, fifteen non-synonymous mutations were identified in the Reunion strains, including one in the capsid and the others in nonstructural proteins (NS) (three in NS1, two in NS2B, one in NS3, one in NS4B, and seven in NS5). CONCLUSION: In contrast to what was seen in previous outbreaks, recent DENV-1 outbreaks in Reunion and the Seychelles were caused by distinct genotypes, all likely originating from Asia where dengue is (hyper)endemic in many countries. Epidemic DENV-1 strains from Reunion harbored specific non-synonymous mutations whose biological significance needs to be further investigated.

Severe SARS-CoV-2 infection as a marker of undiagnosed cancer: a population-based study.

No study has yet investigated if a severe SARS-CoV-2 infection represents a marker of an undiagnosed cancer. This population-based study, using the SNDS database, identified from 02/15/2020 to 08/31/2021, 41,302 individuals hospitalized in intensive care unit due to SARS-CoV-2 (ICU-gr) and 713,670 control individuals not hospitalized for SARS-CoV-2 (C-gr). Individuals were matched according to year of birth, sex and French department. The cancer incidence was compared in the two groups during the follow-up period (index date-12/31/2021), using Cox proportional hazards models adjusted on matching variables, socioeconomic characteristics and comorbidities. In the ICU-gr, 2.2% (n = 897) was diagnosed with a cancer in the following months, compared to 1.5% (n = 10,944) in the C-gr. The ICU-gr had a 1.31 higher risk of being diagnosed with a cancer following hospital discharge compared to the C-gr (aHR 1.31, 95% CI 1.22-1.41). A global similar trend was found when competing risk of death was taken into account (aHR 1.25, 95% CI 1.16-1.34). A significant higher risk was found concerning renal (aHR 3.16, 95% CI 2.33-4.27), hematological (aHR 2.54, 95% CI 2.07-3.12), colon (aHR 1.72, 95% CI 1.34-2.21), and lung (aHR 1.70, 95% CI 1.39-2.08) cancers. This suggests that a severe SARS-CoV-2 infection may represent a marker of an undiagnosed cancer.

Social media and internet search data to inform drug utilization: A systematic scoping review.

Introduction: Drug utilization is currently assessed through traditional data sources such as big electronic medical records (EMRs) databases, surveys, and medication sales. Social media and internet data have been reported to provide more accessible and more timely access to medications' utilization. Objective: This review aims at providing evidence comparing web data on drug utilization to other sources before the COVID-19 pandemic. Methods: We searched Medline, EMBASE, Web of Science, and Scopus until November 25th, 2019, using a predefined search strategy. Two independent reviewers conducted screening and data extraction. Results: Of 6,563 (64%) deduplicated publications retrieved, 14 (0.2%) were included. All studies showed positive associations between drug utilization information from web and comparison data using very different methods. A total of nine (64%) studies found positive linear correlations in drug utilization between web and comparison data. Five studies reported association using other methods: One study reported similar drug popularity rankings using both data sources. Two studies developed prediction models for future drug consumption, including both web and comparison data, and two studies conducted ecological analyses but did not quantitatively compare data sources. According to the STROBE, RECORD, and RECORD-PE checklists, overall reporting quality was mediocre. Many items were left blank as they were out of scope for the type of study investigated. Conclusion: Our results demonstrate the potential of web data for assessing drug utilization, although the field is still in a nascent period of investigation. Ultimately, social media and internet search data could be used to get a quick preliminary quantification of drug use in real time. Additional studies on the topic should use more standardized methodologies on different sets of drugs in order to confirm these findings. In addition, currently available checklists for study quality of reporting would need to be adapted to these new sources of scientific information.

Investigation of Dengue Infection in Asymptomatic Individuals during a Recent Outbreak in La Réunion.

The number of dengue cases has increased dramatically over the past 20 years and is an important concern, particularly as the trends toward urbanization continue. While the majority of dengue cases are thought to be asymptomatic, it is unknown to what extent these contribute to transmission. A better understanding of their importance would help to guide control efforts. In 2019, a dengue outbreak in La Reunion resulted in more than 18,000 confirmed cases. Between October 2019 and August 2020, 19 clusters were investigated in the south, west, and east of the island, enabling the recruitment of 605 participants from 368 households within a 200 m radius of the home of the index cases (ICs). No active asymptomatic infections confirmed by RT-PCR were detected. Only 15% were possible asymptomatic dengue infections detected by the presence of anti-dengue IgM antibodies. Only 5.3% of the participants had a recent dengue infection confirmed by RT-PCR. Although the resurgence of dengue in La Réunion is very recent (2016), the rate of anti-dengue IgG positivity, a marker of past infections, was already high at 43% in this study. Dengue transmission was focal in time and space, as most cases were detected within a 100-m radius of the ICs, and within a time interval of less than 7 days between infections detected in a same cluster. No particular demographic or socio-cultural characteristics were associated with dengue infections. On the other hand, environmental risk factors such as type of housing or presence of rubbish in the streets were associated with dengue infections.

Indoor Air Quality and COVID-19: A Scoping Review.

Objectives: The COVID-19 pandemic has been a major public health concern for the past 3 years. Scientific evidence on the relationship between SARS-CoV-2 infection and indoor air quality still needs to be demonstrated. This scoping review aims to study the association between air quality indoors and COVID-19. Methods: A scoping review analyzing the association between indoor air quality and epidemiological outcomes was conducted. Papers published between 1 January 2020 and 31 October 2022 were included. Hospital settings were excluded from the study. Results: Eight relevant articles met the inclusion criteria. Indoor settings included workplaces, schools, restaurants, and public transport. Types of ventilation used to improve indoor air quality were dilution methods (opening windows) and mechanical systems with or without filtration or purifier. CO2 sensors were employed in one study. All the studies showed a positive association between indoor air quality and its improvement and epidemiological indicators. Conclusion: The findings of this scoping review indicate that indoor air quality, which can be improved with ventilation methods, may reduce the risk of developing COVID-19. Ventilation could thus be viewed as a possible effective mitigating method.

The End of the Elimination Strategy: Decisive Factors towards Sustainable Management of COVID-19 in New Zealand.

New Zealand has long been praised for the effectiveness of its COVID-19 elimination strategy. It resulted in fewer COVID-19-related deaths, better economic recovery, and less stringent policy measures within its borders compared with other OECD countries, which opted for mitigation or suppression. However, since September 2021, the rising number of infections has not been contained anymore by the contact tracing and self-isolation system in place and the government has shifted towards a policy strategy similar to suppression to manage the crisis. In this case study, we analyse the factors that led the government to switch policy and discuss why elimination became unsustainable to manage the COVID-19 epidemic in New Zealand. Results showed that the socioeconomic and political factors, along with the appearance of new variants and a delayed vaccination program, were accountable for the switch in strategy. This switch allows the country to better adapt to the evolving nature of the disease and to address the social and economic repercussions of the first year of measures. Our conclusion does not disregard elimination as an appropriate initial strategy to contain this pandemic in the absence of a vaccine or treatment, but rather suggests that borders cannot remain closed for long periods of time without creating social, economical, and political issues.