Contact tracing management of a measles case in a paediatric hospital: experience of the local public health unit, Portugal, January 2024.

In January 2024, a child was diagnosed with measles in a paediatric hospital in Lisbon. Of 123 contacts, 39 (32%) were not fully immunised, presenting a risk for a potential outbreak. The public health unit initiated control measures and identified challenges during the response, such as the lack of interoperability between information systems and accessing vaccination records. The lessons learned prompted changes to national contact tracing procedures for measles, further strengthening Portugal's preparedness.

Requests, Issuing, and Hospital Admissions Regarding Mental Health Warrants Before and During the COVID-19 Pandemic in a Region in Portugal.

INTRODUCTION: Mental health warrants exist in most countries and are issued when patients have severe mental illness, refuse treatment, and present a serious risk to themselves or others. We describe the epidemiology of mental health warrant requests received, and warrants issued by a Public Health Unit in a Portuguese region, as well as subsequent hospital admissions before and during the COVID-19 pandemic. METHODS: We used routine administrative data of mental health warrant request entries from a Public Health Unit serving a population of 219 739 individuals and compared the average of monthly requests, issued warrants, and hospital admissions during two separate periods (January 2013 to January 2021 and February 2021 to October 2022) as well as the proportion of warrants issued, hospital admissions among requests, and other patient characteristics. We identified factors associated with hospital admissions among the requests using logistic regression. RESULTS: Monthly average warrant requests, issued warrants and hospital admissions increased after February 2021 (x̄ 2.87 vs 7.09 p < 0.001; x̄ 2.67 vs 6.42 p < 0.001; x̄ 1.55 vs 3.58 p < 0.001). We found no differences by period in the proportion of requests with issued warrants (92.8% vs 90.6% p = 0.42) nor the proportion of requests with subsequent hospital admissions (54.0% vs 49.0% p = 0.33). In the second period, there were differences in the proportion of patients with a previously diagnosed mental health disorder (95.3% vs 90.4% p = 0.049). There were significant differences in the distribution of the origin of requests. Being unemployed (OR:2.5 CI:1.2 - 5.2), not having completed high school (OR:2.01 CI:1.12 - 3.77) and having university education (OR:3.67 CI:1.27 - 10.57) degree were associated with hospital admission. CONCLUSION: Severe mental illness with criteria for mental health warrants may require more resources and different approaches due to a possible increase during and after the COVID-19 pandemic. Community based mental healthcare, incentivized follow-up by primary care and ambulatory treatment may be considered. Further research should evaluate both the national and international trends and associated factors.

Difference in determinants of ICU admission and death among COVID-19 hospitalized patients in two epidemic waves in Portugal: possible impact of healthcare burden and hospital bed occupancy on clinical management and outcomes, March-December 2020.

Aim: Identify factors associated with COVID-19 intensive care unit (ICU) admission and death among hospitalized cases in Portugal, and variations from the first to the second wave in Portugal, March-December 2020. Introduction: Determinants of ICU admission and death for COVID-19 need further understanding and may change over time. We used hospital discharge data (ICD-10 diagnosis-related groups) to identify factors associated with COVID-19 outcomes in two epidemic periods with different hospital burdens to inform policy and practice. Methods: We conducted a retrospective cohort study including all hospitalized cases of laboratory-confirmed COVID-19 in the Portuguese NHS hospitals, discharged from March to December 2020. We calculated sex, age, comorbidities, attack rates by period, and calculated adjusted relative risks (aRR) for the outcomes of admission to ICU and death, using Poisson regressions. We tested effect modification between two distinct pandemic periods (March-September/October-December) with lower and higher hospital burden, in other determinants. Results: Of 18,105 COVID-19 hospitalized cases, 10.22% were admitted to the ICU and 20.28% died in hospital before discharge. Being aged 60-69 years (when compared with those aged 0-49) was the strongest independent risk factor for ICU admission (aRR 1.91, 95%CI 1.62-2.26). Unlike ICU admission, risk of death increased continuously with age and in the presence of specific comorbidities. Overall, the probability of ICU admission was reduced in the second period but the risk of death did not change. Risk factors for ICU admission and death differed by epidemic period. Testing interactions, in the period with high hospital burden, those aged 80-89, women, and those with specific comorbidities had a significantly lower aRR for ICU admission. Risk of death increased in the second period for those with dementia and diabetes. Discussion and conclusions: The probability of ICU admission was reduced in the second period. Different patient profiles were identified for ICU and deaths among COVID-19-hospitalized patients in different pandemic periods with lower and higher hospital burden, possibly implying changes in clinical practice, priority setting, or clinical presentation that should be further investigated and discussed considering impacts of higher burden on services in health outcomes, to inform preparedness, healthcare workforce planning, and pandemic prevention measures.

COVID-19 surveillance: Large decrease in clinical notifications and epidemiological investigation questionnaires for laboratory-confirmed cases after the 2nd epidemic wave, Portugal March 2020-July 2021.

Introduction: In Portugal, COVID-19 laboratory notifications, clinical notifications (CNs), and epidemiological investigation questionnaires (EI) were electronically submitted by laboratories, clinicians, and public health professionals, respectively, to the Portuguese National Epidemiological Surveillance System (SINAVE), as mandated by law. We described CN and EI completeness in SINAVE to inform pandemic surveillance efforts. Methods: We calculated the proportion of COVID-19 laboratory-notified cases without CN nor EI, and without EI by region and age group, in each month, from March 2020 to July 2021. We tested the correlation between those proportions and monthly case counts in two epidemic periods and used Poisson regression to identify factors associated with the outcomes. Results: The analysis included 909,720 laboratory-notified cases. After October 2020, an increase in the number of COVID-19 cases was associated with a decrease in the submissions of CN and EI. By July 2021, 68.57% of cases had no associated CN nor EI, and 96.26% had no EI. Until January 2021, there was a positive correlation between monthly case counts and the monthly proportion of cases without CN nor EI and without EI, but not afterward. Cases aged 75 years or older had a lower proportion without CN nor EI (aRR: 0.842 CI95% 0.839-0.845). When compared to the Norte region, cases from Alentejo, Algarve, and Madeira had a lower probability of having no EI (aRR;0.659 CI 95%0.654-0.664; aRR 0.705 CI 95% 0.7-0.711; and aRR 0.363 CI 95% 0.354-0.373, respectively). Discussion: After January 2021, CN and EI were submitted in a small proportion of laboratory-confirmed cases, varying by age and region. Facing the large number of COVID-19 cases, public health services may have adopted other registry strategies including new surveillance and management tools to respond to operational needs. This may have contributed to the abandonment of official CN and EI submission. Useful knowledge on the context of infection, symptom profile, and other knowledge gaps was no longer adequately supported by SINAVE. Regular evaluation of pandemic surveillance systems' completeness is necessary to inform surveillance improvements and procedures considering dynamic objectives, usefulness, acceptability, and simplicity.

[Pre-Exposure Prophylaxis for Human Immunodeficiency Virus in the Medical Curricula in Portugal: A Cross-Sectional Analysis].

INTRODUCTION: Pre-exposure prophylaxis (PrEP) has gained relevance as a method of prevention for HIV in certain people and settings. Following the publication of the guideline on PrEP prescribing in Portugal, we aimed to assess the knowledge of Portuguese Medical Students about PrEP. MATERIAL AND METHODS: An online survey was sent to Medical students of Portuguese Medical Schools. We conducted a descriptive analysis of the results and an analytic cross-sectional study to identify factors associated with "knowing about PrEP", "having had one class about PrEP" and "identifying eligible groups correctly". RESULTS: Of the 796 students that responded to the survey, 64.6% were aware of what PrEP is. Of these, 34.44% acquired this knowledge during their training. Out of the total amount of respondents, 4.77% could identify correctly and completely the eligible groups for PrEP. As the training years went by, the probability of being aware of PrEP, having had one class about PrEP, and identifying the eligible groups correctly, increased. Of the sixth-year students, 43.48% had had one class about PrEP and among the students that were aware of PrEP, 28% identified what the eligible groups were. After adjusting for the school year, we found differences between Medical Schools regarding the outcomes. The association between the different ways of learning about PrEP and the ability to correctly identify eligible groups for PrEP was not statistically significant. CONCLUSION: The differences between Medical Schools could be harmonized through changes in the medical curricula that would allow this topic to be addressed more often.

Introdução: A profilaxia pré-exposição (PrEP) ganhou relevância como método de prevenção do VIH em determinados indivíduos e contextos. Após a entrada em vigor das normas para prescrição em Portugal, pretendemos aferir o conhecimento em relação à PrEP entre os estudantes de Medicina em Portugal.Material e Métodos: Foi enviado um questionário online aos estudantes de Medicina das escolas médicas portuguesas. Foi feita uma análise descritiva dos resultados e um estudo transversal analítico para identificar fatores associados a "conhecer a PrEP", "ter tido uma aula de PrEP", e "identificar grupos elegíveis corretamente".Resultados: Dos 796 estudantes que responderam, 64,6% sabiam o que era a PrEP. Destes, 34,44% obteve conhecimento sobre a mesma durante a sua formação. Entre os respondentes, 4,77% identificaram correta e completamente os grupos elegíveis. Com o avançar do ano letivo, a probabilidade de conhecer a PrEP, ter tido uma aula de PrEP e identificar os grupos corretamente aumentava. No sexto ano, 43,48% tinham tido uma aula sobre PrEP e entre os que conheciam a PrEP, 28% identificaram os grupos elegíveis. Existem diferenças entre as escolas médicas após ajustamento para o ano letivo em relação aos resultados obtidos. A forma como se tomou conhecimento da PrEP não alterou de forma estatisticamente significativa a capacidade de identificar corretamente grupos elegíveisConclusão: As diferenças entre as escolas médicas poderão ser harmonizadas. Esta temática poderá ser reforçada nos respetivos currículos.

Determinants for hospitalisations, intensive care unit admission and death among 20,293 reported COVID-19 cases in Portugal, March to April 2020.

BackgroundDeterminants of hospitalisation, intensive care unit (ICU) admission and death are still unclear for COVID-19. Few studies have adjusted for confounding for different clinical outcomes including all reported cases within a country.AimWe used routine surveillance data from Portugal to identify risk factors for severe COVID-19 outcomes, and to support risk stratification, public health interventions, and planning of healthcare resources.MethodsWe conducted a retrospective cohort study including 20,293 laboratory-confirmed cases of COVID-19 reported between 1 March and 28 April 2020 through the national epidemiological surveillance system. We calculated absolute risk, relative risk (RR) and adjusted relative risk (aRR) to identify demographic and clinical factors associated with hospitalisation, ICU admission and death using Poisson regressions.ResultsIncreasing age (≥ 60 years) was the major determinant for all outcomes. Age ≥ 90 years was the strongest determinant of hospital admission (aRR: 6.1), and 70-79 years for ICU (aRR: 10.4). Comorbidities of cardiovascular, immunodeficiency, kidney and lung disease (aRR: 4.3, 2.8, 2.4, 2.0, respectively) had stronger associations with ICU admission, while for death they were kidney, cardiovascular and chronic neurological disease (aRR: 2.9, 2.6, 2.0).ConclusionsOlder age was the strongest risk factor for all severe outcomes. These findings from the early stages of the COVID-19 pandemic support risk-stratified public health measures that should prioritise protecting older people. Epidemiological scenarios and clinical guidelines should consider this, even though under-ascertainment should also be considered.

Initial Assessment of the Impact of the Emergency State Lockdown Measures on the 1st Wave of the COVID-19 Epidemic in Portugal.

INTRODUCTION: Portugal took early action to control the COVID-19 epidemic, initiating lockdown measures on March 16th when it recorded only 62 cases of COVID-19 per million inhabitants and reported no deaths. The Portuguese public complied quickly, reducing their overall mobility by 80%. The aim of this study was to estimate the initial impact of the lockdown in Portugal in terms of the reduction of the burden on the healthcare system. MATERIAL AND METHODS: We forecasted epidemic curves for: Cases, hospital inpatients (overall and in intensive care), and deaths without lockdown, assuming that the impact of containment measures would start 14 days after initial lockdown was implemented. We used exponential smoothing models for deaths, intensive care and hospitalizations and an ARIMA model for number of cases. Models were selected considering fitness to the observed data up to the 31st March 2020. We then compared observed (with intervention) and forecasted curves (without intervention). RESULTS: Between April 1st and April 15th, there were 146 fewer deaths (-25%), 5568 fewer cases (-23%) and, as of April 15th, there were 519 fewer intensive care inpatients (-69%) than forecasted without the lockdown. On April 15th, the number of intensive care inpatients could have reached 748, three times higher than the observed value (229) if the intervention had been delayed. DISCUSSION: If the lockdown had not been implemented in mid-March, Portugal intensive care capacity (528 beds) would have likely been breached during the first half of April. The lockdown seems to have been effective in reducing transmission of SARS-CoV-2, serious COVID-19 disease, and associated mortality, thus decreasing demand on health services. CONCLUSION: An early lockdown allowed time for the National Health Service to mobilize resources and acquire personal protective equipment, increase testing, contact tracing and hospital and intensive care capacity and to promote broad prevention and control measures. When lifting more stringent measures, strong surveillance and communication strategies that mobilize individual prevention efforts are necessary.

Introdução: Portugal tomou cedo medidas para controlar a epidemia de COVID-19, impondo medidas de confinamento a partir de 16 de março, quando registava apenas 62 casos de COVID-19 por milhão de habitantes e nenhuma morte. Os portugueses seguiram as recomendações reduzindo sua mobilidade em 80%. O objectivo deste estudo foi estimar o impacto do confinamento em Portugal com foco na redução do impacto nos serviço de saúde. Material e Métodos: Fizemos previsões para as curvas epidémicas de casos, internamento hospitalares (geral e em unidades de cuidados intensivos) e óbitos sem confinamento, assumindo que o impacto das medidas de contenção começaria 14 dias após o início das medidas. Utilizámos modelos de alisamento exponencial para óbitos, internados em cuidados intensivos e total de internados e um modelo ARIMA para número de novos casos. Os modelos foram selecionados considerando adequação aos dados observados até 31 de março de 2020. Em seguida, comparámos as curvas observadas (com intervenção) e previstas (sem intervenção). Resultados: Entre 1 e 15 de abril houve 146 menos mortes (-25%), 5568 menos casos (-23%) e, em 15 de abril, houve 519 menos internamentos em unidades de cuidados intensivos (-69%) e 508 menos doentes no total de internados (-28%) do que o previsto sem confinamento. Em 15 de abril, o número de pacientes internados na unidades de cuidados intensivos poderia ter atingido 748, três vezes maior que o valor observado (229) se a intervenção tivesse sido adiada. Discussão: Se o confinamento não tivesse sido implementado em meados de março, a capacidade de unidades de cuidados intensivos em Portugal (528 camas) teria provavelmente sido ultrapassada na primeira quinzena de abril. O confinamento parece ter sido eficaz na redução de infeções, doença grave e mortalidade associada, diminuindo a procura de serviços de saúde. Conclusão: Um confinamento antecipado permitiu comprar tempo para o Serviço Nacional de Saúde mobilizar recursos e adquirir equipamentos de proteção individual, aumentar a capacidade de testar e realizar rastreio de contactos, preparar-se para um aumento da procura hospitalar e de unidades de cuidados intensivos e promover amplas medidas de prevenção e controlo. Ao levantar medidas mais restritivas será importante manter uma vigilância epidemiológica e estratégias de comunicaçao robustas que mobilizem comportamentos individuais preventivos.