Modeling geographic vaccination strategies for COVID-19 in Norway.

Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient vaccine allocation to reduce infections and severe outcomes. This study explored alternative vaccination strategies to minimize health outcomes (infections, hospitalizations, ICU admissions, deaths) by varying regions prioritized, extra doses prioritized, and implementation start time. Using two models (individual-based and meta-population), we simulated COVID-19 transmission during the primary vaccination period in Norway, covering the first 7 months of 2021. We investigated alternative strategies to allocate more vaccine doses to regions with a higher force of infection. We also examined the robustness of our results and highlighted potential structural differences between the two models. Our findings suggest that early vaccine prioritization could reduce COVID-19 related health outcomes by 8% to 20% compared to a baseline strategy without geographic prioritization. For minimizing infections, hospitalizations, or ICU admissions, the best strategy was to initially allocate all available vaccine doses to fewer high-risk municipalities, comprising approximately one-fourth of the population. For minimizing deaths, a moderate level of geographic prioritization, with approximately one-third of the population receiving doubled doses, gave the best outcomes by balancing the trade-off between vaccinating younger people in high-risk areas and older people in low-risk areas. The actual strategy implemented in Norway was a two-step moderate level aimed at maintaining the balance and ensuring ethical considerations and public trust. However, it did not offer significant advantages over the baseline strategy without geographic prioritization. Earlier implementation of geographic prioritization could have more effectively addressed the main wave of infections, substantially reducing the national burden of the pandemic.

A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting.

The COVID-19 pandemic is challenging nations with devastating health and economic consequences. The spread of the disease has revealed major geographical heterogeneity because of regionally varying individual behaviour and mobility patterns, unequal meteorological conditions, diverse viral variants, and locally implemented non-pharmaceutical interventions and vaccination roll-out. To support national and regional authorities in surveilling and controlling the pandemic in real-time as it unfolds, we here develop a new regional mathematical and statistical model. The model, which has been in use in Norway during the first two years of the pandemic, is informed by real-time mobility estimates from mobile phone data and laboratory-confirmed case and hospitalisation incidence. To estimate regional and time-varying transmissibility, case detection probabilities, and missed imported cases, we developed a novel sequential Approximate Bayesian Computation method allowing inference in useful time, despite the high parametric dimension. We test our approach on Norway and find that three-week-ahead predictions are precise and well-calibrated, enabling policy-relevant situational awareness at a local scale. By comparing the reproduction numbers before and after lockdowns, we identify spatially heterogeneous patterns in their effect on the transmissibility, with a stronger effect in the most populated regions compared to the national reduction estimated to be 85% (95% CI 78%-89%). Our approach is the first regional changepoint stochastic metapopulation model capable of real time spatially refined surveillance and forecasting during emergencies.

Social contact patterns during the early COVID-19 pandemic in Norway: insights from a panel study, April to September 2020.

BACKGROUND: During the COVID-19 pandemic, many countries adopted social distance measures and lockdowns of varying strictness. Social contact patterns are essential in driving the spread of respiratory infections, and country-specific measurements are needed. This study aimed to gain insights into changes in social contacts and behaviour during the early pandemic phase in Norway. METHODS: We conducted an online panel study among a nationally representative sample of Norwegian adults by age and gender. The panel study included six data collections waves between April and September 2020, and 2017 survey data from a random sample of the Norwegian population (including children < 18 years old) were used as baseline. The market research company Ipsos was responsible for carrying out the 2020 surveys. We calculated mean daily contacts, and estimated age-stratified contact matrices during the study period employing imputation of child-to-child contacts. We used the next-generation method to assess the relative reduction of R0 and compared the results to reproduction numbers estimated for Norway during the 2020 study period. RESULTS: Over the six waves in 2020, 5 938 observations/responses were registered from 1 718 individuals who reported data on 22 074 contacts. The mean daily number of contacts among adults varied between 3.2 (95%CI 3.0-3.4) to 3.9 (95%CI 3.6-4.2) across the data collection waves, representing a 67-73% decline compared to pre-pandemic levels (baseline). Fewer contacts in the community setting largely drove the reduction; the drop was most prominent among younger adults. Despite gradual easing of social distance measures during the survey period, the estimated population contact matrices remained relatively stable and displayed more inter-age group mixing than at baseline. Contacts within households and the community outside schools and workplaces contributed most to social encounters. Using the next-generation method R0 was found to be roughly 25% of pre-pandemic levels during the study period, suggesting controlled transmission. CONCLUSION: Social contacts declined significantly in the months following the March 2020 lockdown, aligning with implementation of stringent social distancing measures. These findings contribute valuable empirical information into the social behaviour in Norway during the early pandemic, which can be used to enhance policy-relevant models for addressing future crises when mitigation measures might be implemented.

Effects of non-compulsory and mandatory COVID-19 interventions on travel distance and time away from home, Norway, 2021.

BackgroundGiven the societal, economic and health costs of COVID-19 non-pharmaceutical interventions (NPI), it is important to assess their effects. Human mobility serves as a surrogate measure for human contacts and compliance with NPI. In Nordic countries, NPI have mostly been advised and sometimes made mandatory. It is unclear if making NPI mandatory further reduced mobility.AimWe investigated the effect of non-compulsory and follow-up mandatory measures in major cities and rural regions on human mobility in Norway. We identified NPI categories that most affected mobility.MethodsWe used mobile phone mobility data from the largest Norwegian operator. We analysed non-compulsory and mandatory measures with before-after and synthetic difference-in-differences approaches. By regression, we investigated the impact of different NPI on mobility.ResultsNationally and in less populated regions, time travelled, but not distance, decreased after follow-up mandatory measures. In urban areas, however, distance decreased after follow-up mandates, and the reduction exceeded the decrease after initial non-compulsory measures. Stricter metre rules, gyms reopening, and restaurants and shops reopening were significantly associated with changes in mobility.ConclusionOverall, distance travelled from home decreased after non-compulsory measures, and in urban areas, distance further decreased after follow-up mandates. Time travelled reduced more after mandates than after non-compulsory measures for all regions and interventions. Stricter distancing and reopening of gyms, restaurants and shops were associated with changes in mobility.

A compelling demonstration of why traditional statistical regression models cannot be used to identify risk factors from case data on infectious diseases: a simulation study.

BACKGROUND: Regression models are often used to explain the relative risk of infectious diseases among groups. For example, overrepresentation of immigrants among COVID-19 cases has been found in multiple countries. Several studies apply regression models to investigate whether different risk factors can explain this overrepresentation among immigrants without considering dependence between the cases. METHODS: We study the appropriateness of traditional statistical regression methods for identifying risk factors for infectious diseases, by a simulation study. We model infectious disease spread by a simple, population-structured version of an SIR (susceptible-infected-recovered)-model, which is one of the most famous and well-established models for infectious disease spread. The population is thus divided into different sub-groups. We vary the contact structure between the sub-groups of the population. We analyse the relation between individual-level risk of infection and group-level relative risk. We analyse whether Poisson regression estimators can capture the true, underlying parameters of transmission. We assess both the quantitative and qualitative accuracy of the estimated regression coefficients. RESULTS: We illustrate that there is no clear relationship between differences in individual characteristics and group-level overrepresentation -small differences on the individual level can result in arbitrarily high overrepresentation. We demonstrate that individual risk of infection cannot be properly defined without simultaneous specification of the infection level of the population. We argue that the estimated regression coefficients are not interpretable and show that it is not possible to adjust for other variables by standard regression methods. Finally, we illustrate that regression models can result in the significance of variables unrelated to infection risk in the constructed simulation example (e.g. ethnicity), particularly when a large proportion of contacts is within the same group. CONCLUSIONS: Traditional regression models which are valid for modelling risk between groups for non-communicable diseases are not valid for infectious diseases. By applying such methods to identify risk factors of infectious diseases, one risks ending up with wrong conclusions. Output from such analyses should therefore be treated with great caution.

Risk conditions in children hospitalized with influenza in Norway, 2017-2019.

BACKGROUND: Norwegian children are more frequently hospitalized with influenza than adults. Little is known about the characteristics of these children. Our aim was to investigate the presence of pre-existing risk conditions and to determine the duration of influenza hospitalizations in children during two influenza seasons. METHODS: The Norwegian Patient Registry holds data on all hospitalized patients in Norway. We included all patients younger than 18 years hospitalized with a diagnosis of influenza during the influenza seasons 2017-18 and 2018-19. Pre-existing risk conditions for influenza were identified by ICD-10 diagnoses in the Norwegian Patient Registry. In addition, information on asthma diagnoses were also retrieved from the Norwegian Registry for Primary Health Care. To estimate the prevalence of risk conditions in the child population, we obtained diagnoses on all Norwegian children in a two-year period prior to each influenza season. We calculated age-specific rates for hospitalization and risk for being hospitalized with influenza in children with risk conditions. RESULTS: In total, 1013 children were hospitalized with influenza during the two influenza seasons. Children younger than 6 months had the highest rate of hospitalization, accounting for 13.5% of all admissions (137 children). Hospitalization rates decreased with increasing age. Among children hospitalized with influenza, 25% had one or more pre-existing risk conditions for severe influenza, compared to 5% in the general population under 18 years. Having one or more risk conditions significantly increased the risk of hospitalization, (Odds Ratio (OR) 6.1, 95% confidence interval (CI) 5.0-7.4 in the 2017-18 season, and OR 6.8, 95% CI 5.4-8.4 in the 2018-19 season). Immunocompromised children and children with epilepsy had the highest risk of hospitalization with influenza, followed by children with heart disease and lung disease. The average length of stay in hospital were 4.6 days, and this did not differ with age. CONCLUSION: Children with pre-existing risk conditions for influenza had a higher risk of hospitalization for influenza. However, most children (75%) admitted to hospital with influenza in Norway during 2017-2019 did not have pre-existing risk conditions. Influenza vaccination should be promoted in particular for children with risk conditions and pregnant women to protect new-borns.

Modelling the burden of hepatitis C infection among people who inject drugs in Norway, 1973-2030.

BACKGROUND: Lack of Hepatitis C virus (HCV) incidence data in (Norwegian) high-risk groups impedes the ability to make informed decisions on prevention measures. Thus we rely on modelling to estimate the incidence and burden of HCV infections. METHODS: We constructed a compartmental model for HCV infections in Norway among active and former people who inject drugs (PWIDs). We based yearly transition rates on literature. The model was fitted to absolute numbers of hepatitis C associated cirrhosis, hepatocellular carcinoma (HCC) and death from national data sources (2000-2013). We estimated the number (95%CI) of HCV infections, cirrhosis, HCC and death and disability adjusted life years (DALYs) due to HCV infections in Norway, 1973-2030. We assumed treatment rates in the projected period were similar to those in 2013. RESULTS: The estimated proportion of chronic HCV (including those with cirrhosis and HCC) among PWIDs was stable from 2000 (49%; 4441/9108) to 2013 (43%; 3667/8587). We estimated that the incidence of HCV among PWIDs was 381 new infections in 2015. The estimated number of people with cirrhosis, HCC, and liver transplant was predicted to increase until 2022 (1537 people). DALYs among active PWIDs estimated to peak in 2006 (3480 DALYs) and decrease to 1870 DALYs in 2030. Chronic HCV infection contributes most to the total burden of HCV infection, and peaks at 1917 DALYs (52%) in 2007. The burden of HCV related to PWID increased until 2006 with 81/100,000 DALYs inhabitants and decreased to 68/100,000 DALYs in 2015. CONCLUSION: The burden of HCV associated with injecting drug use is considerable, with chronic HCV infection contributing most to the total burden. This model can be used to estimate the impact of different interventions on the HCV burden in Norway and to perform cost-benefit analyses of various public health measures.

Association between heavy precipitation events and waterborne outbreaks in four Nordic countries, 1992-2012.

We conducted a matched case-control study to examine the association between heavy precipitation events and waterborne outbreaks (WBOs) by linking epidemiological registries and meteorological data between 1992 and 2012 in four Nordic countries. Heavy precipitation events were defined by above average (exceedance) daily rainfall during the preceding weeks using local references. We performed conditional logistic regression using the four previous years as the controls. Among WBOs with known onset date (n = 89), exceedance rainfall on two or more days was associated with occurrence of outbreak, OR = 3.06 (95% CI 1.38-6.78), compared to zero exceedance days. Stratified analyses revealed a significant association with single household water supplies, ground water as source and for outbreaks occurring during spring and summer. These findings were reproduced in analyses including all WBOs with known outbreak month (n = 186). The vulnerability of single households to WBOs associated with heavy precipitation events should be communicated to homeowners and implemented into future policy planning to reduce the risk of waterborne illness.

Influenza in workplaces: transmission, workers' adherence to sick leave advice and European sick leave recommendations.

BACKGROUND: Knowledge about influenza transmission in the workplace and whether staying home from work when experiencing influenza-like illness can reduce the spread of influenza is crucial for the design of efficient public health initiatives. AIM: This review synthesizes current literature on sickness presenteeism and influenza transmission in the workplace and provides an overview of sick leave recommendations in Europe for influenza. METHODS: A search was performed on Medline, Embase, PsychINFO, Cinahl, Web of Science, Scopus and SweMed to identify studies related to workplace contacts, -transmission, -interventions and compliance with recommendations to take sick leave. A web-based survey on national recommendations and policies for sick leave during influenza was issued to 31 European countries. RESULTS: Twenty-two articles (9 surveys; 13 modelling articles) were eligible for this review. Results from social mixing studies suggest that 20-25% of weekly contacts are made in the workplace, while modelling studies suggest that on average 16% (range 9-33%) of influenza transmission occurs in the workplace. The effectiveness of interventions to reduce workplace presenteeism is largely unknown. Finally, estimates from studies reporting expected compliance with sick leave recommendations ranged from 71 to 95%. Overall, 18 countries participated in the survey of which nine (50%) had issued recommendations encouraging sick employees to stay at home during the 2009 A(H1N1) pandemic, while only one country had official recommendations for seasonal influenza. CONCLUSIONS: During the 2009 A(H1N1) pandemic, many European countries recommended ill employees to take sick leave. Further research is warranted to quantify the effect of reduced presenteeism during influenza illness.

[Waterborne outbreaks in Norway 2003-2012]. / Vannbårne utbrudd i Norge i perioden 2003-12.

BACKGROUND: We describe the status of waterborne outbreaks notified in Norway and discuss this in the context of outbreaks recorded in previous years, to gain a better understanding of their development in Norway in recent years. MATERIAL AND METHOD: We have collected information on all outbreaks notified to the Norwegian Institute of Public Health via the surveillance system for communicable diseases in the ten-year period from 2003-2012 for which drinking water was given as the suspected cause. RESULTS: Altogether 28 waterborne outbreaks with a total of 8,060 persons reported as ill were notified in the period. The majority of outbreaks resulted in fewer than 100 cases of illness. There were two outbreaks with more than 1,000 cases of illness: an oubreak of campylobacteriosis in Røros and an oubreak of giardiasis in Bergen. In more than half of the outbreaks, water was supplied from public water distribution systems (16/28 outbreaks, 57%). In addition, a large proportion was linked to individual households with their own water supply (12/28 outbreaks, 43%). INTERPRETATION: Most of the outbreaks in the ten-year period were linked to public water distribution systems, while almost half were linked to non-disinfected water supplies to individual households. Although most of the outbreaks were small, two extensive outbreaks were also registered in the period, resulting in more than one thousand cases of illness. This underscores the need for good contingency planning and surveillance, so that suspicion of waterborne outbreaks is rapidly notified to the responsible authorities, and the importance of good protection of water sources, as well as proper maintenance of water treatment plants and distribution systems.

A model for global diversity in response to temperature change over geological time scales, with reference to planktic organisms.

There are strong propositions in the literature that abiotic factors override biotic drivers of diversity on time scales of the fossil record. In order to study the interaction of biotic and abiotic forces on long term changes, we devise a spatio-temporal discrete-time Markov process model of macroevolution featuring population formation, speciation, migration and extinction, where populations are free to migrate. In our model, the extinction probability of these populations is controlled by latitudinally and temporally varying environment (temperature) and competition. Although our model is general enough to be applicable to disparate taxa, we explicitly address planktic organisms, which are assumed to disperse freely without barriers over the Earth's oceans. While rapid and drastic environmental changes tend to eliminate many species, generalists preferentially survive and hence leave generalist descendants. In other words, environmental fluctuations result in generalist descendants which are resilient to future environmental changes. Periods of stable or slow environmental changes lead to more specialist species and higher population numbers. Simulating Cenozoic diversity dynamics with both competition and the environmental component of our model produces diversity curves that reflect current empirical knowledge, which cannot be obtained with just one component. Our model predicts that the average temperature optimum at which planktic species thrive best has declined over the Neogene, following the trend of global average temperatures.

Analytical studies assessing the association between extreme precipitation or temperature and drinking water-related waterborne infections: a review.

Determining the role of weather in waterborne infections is a priority public health research issue as climate change is predicted to increase the frequency of extreme precipitation and temperature events. To document the current knowledge on this topic, we performed a literature review of analytical research studies that have combined epidemiological and meteorological data in order to analyze associations between extreme precipitation or temperature and waterborne disease.A search of the databases Ovid MEDLINE, EMBASE, SCOPUS and Web of Science was conducted, using search terms related to waterborne infections and precipitation or temperature. Results were limited to studies published in English between January 2001 and December 2013.Twenty-four articles were included in this review, predominantly from Asia and North-America. Four articles used waterborne outbreaks as study units, while the remaining articles used number of cases of waterborne infections. Results presented in the different articles were heterogeneous. Although most of the studies identified a positive association between increased precipitation or temperature and infection, there were several in which this association was not evidenced. A number of articles also identified an association between decreased precipitation and infections. This highlights the complex relationship between precipitation or temperature driven transmission and waterborne disease. We encourage researchers to conduct studies examining potential effect modifiers, such as the specific type of microorganism, geographical region, season, type of water supply, water source or water treatment, in order to assess how they modulate the relationship between heavy rain events or temperature and waterborne disease. Addressing these gaps is of primary importance in order to identify the areas where action is needed to minimize negative impact of climate change on health in the future.

Comparing clinical attachment level and pocket depth for predicting periodontal disease progression in healthy sites of patients with chronic periodontitis using multi-state Markov models.

AIM: To understand degeneration of healthy sites and identify factors associated with disease progression in patients with chronic periodontitis. MATERIAL AND METHODS: Data on healthy sites from 163 American and Swedish subjects were analysed using two-three-state (health, gingivitis, chronic periodontitis) Markov models based on bleeding on probing (BOP), and either clinical attachment level (CAL) + BOP or pocket depth (PD) + BOP. RESULTS: In 2 years, 10% (CAL + BOP) and 3% (PD + BOP) of healthy sites developed chronic periodontitis. On average, healthy sites remained healthy for 32 months before transiting in both models. Most transitions (87-97%) from health were to the gingivitis state. The expected duration of the gingivitis lesion was 4-5 months and sites recovered with a high probability (96-98%). Disease severity as measured by number of sites with CAL/PD > 4 mm at baseline and smoking, were associated with fast progression from health to chronic periodontitis within 6 months as were gingival redness in the PD + BOP model only. With age, the rate of disease progression to gingivitis decreased. CONCLUSION: Transition probabilities for gingivitis and chronic periodontitis were higher with CAL + BOP than with PD + BOP. Smoking and disease severity were significant predictors for fast progression.

Antibiotic Consumption in a Cohort of Hospitalized Adults with Viral Respiratory Tract Infection.

Development of antibiotic resistance, a threat to global health, is driven by inappropriate antibiotic usage. Respiratory tract infections (RTIs) are frequently treated empirically with antibiotics, despite the fact that a majority of the infections are caused by viruses. The purpose of this study was to determine the prevalence of antibiotic treatment in hospitalized adults with viral RTIs, and to investigate factors influencing the antibiotic decision-making. We conducted a retrospective observational study of patients ≥ 18 years, hospitalized in 2015-2018 with viral RTIs. Microbiological data were taken from the laboratory information system and information on antibiotic treatment drawn from the hospital records. To investigate decisions for prescribing antibiotic treatment, we evaluated relevant factors such as laboratory and radiological results, in addition to clinical signs. In 951 cases without secondary bacterial RTIs (median age 73 years, 53% female), 720 (76%) were prescribed antibiotic treatment, most frequently beta-lactamase-sensitive penicillins, but cephalosporins were prescribed as first-line in 16% of the cases. The median length of treatment (LOT) in the patients treated with antibiotics was seven days. Patients treated with antibiotics had an average of two days longer hospital stay compared to patients with no such treatment, but no difference in mortality was found. Our study revealed that there is still a role for antimicrobial stewardship to further improve antibiotic use in patients admitted for viral RTIs in a country with relatively low antibiotic consumption.

Modeling the impact of screening policy and screening compliance on incidence and mortality of cervical cancer in the post-HPV vaccination era.

BACKGROUND: In Norway, pap smear screening target women aged 25-69 years on a triennial basis. The introduction of human papillomavirus (HPV) mass immunization in 2009 raises questions regarding the cost-saving future changes to current screening strategies. METHODS: We calibrated a dynamic HPV transmission model to Norwegian data and assessed the impact of changing screening 20 or 30 years after vaccine introduction, assuming 60 or 90% vaccination coverage. Screening compliance among vaccinated women was assumed at 80 or 50%. Strategies considered: (i) 5-yearly screening of women of 25-69 years, (ii) 3-yearly screening of women of 30-69 years and (iii) 3-yearly screening of women of 25-59 years. RESULTS: Greatest health gains were accomplished by ensuring a high vaccine uptake. In 2060, cervical cancer incidence was reduced by an estimated 36-57% compared with that of no vaccination. Stopping screening at the age of 60 years, excluding opportunistic screening, increased cervical cancer incidence by 3% (2060) compared with maintaining the current screening strategy, resulting in 1.0-2.4% extra cancers (2010-2060). The 5-yearly screening strategy elevated cervical cancer incidence by 30% resulting in 4.7-11.3% additional cancers. CONCLUSION: High vaccine uptake in the years to come is of primary concern. Screening of young women <30 years remains important, even under the conditions of high vaccine coverage.

Dynamic modelling of costs and health consequences of school closure during an influenza pandemic.

BACKGROUND: The purpose of this article is to evaluate the cost-effectiveness of school closure during a potential influenza pandemic and to examine the trade-off between costs and health benefits for school closure involving different target groups and different closure durations. METHODS: We developed two models: a dynamic disease model capturing the spread of influenza and an economic model capturing the costs and benefits of school closure. Decisions were based on quality-adjusted life years gained using incremental cost-effectiveness ratios. The disease model is an age-structured SEIR compartmental model based on the population of Oslo. We studied the costs and benefits of school closure by varying the age targets (kindergarten, primary school, secondary school) and closure durations (1-10 weeks), given pandemics with basic reproductive number of 1.5, 2.0 or 2.5. RESULTS: The cost-effectiveness of school closure varies depending on the target group, duration and whether indirect costs are considered. Using a case fatality rate (CFR) of 0.1-0.2% and with current cost-effectiveness threshold for Norway, closing secondary school is the only cost-effective strategy, when indirect costs are included. The most cost-effective strategies would be closing secondary schools for 8 weeks if R0=1.5, 6 weeks if R0=2.0, and 4 weeks if R0= 2.5. For severe pandemics with case fatality rates of 1-2%, similar to the Spanish flu, or when indirect costs are disregarded, the optimal strategy is closing kindergarten, primary and secondary school for extended periods of time. For a pandemic with 2009 H1N1 characteristics (mild severity and low transmissibility), closing schools would not be cost-effective, regardless of the age target of school children. CONCLUSIONS: School closure has moderate impact on the epidemic's scope, but the resulting disruption to society imposes a potentially great cost in terms of lost productivity from parents' work absenteeism.

Influenza hospitalizations during childhood in children born preterm.

OBJECTIVE: The objective is to determine if children born preterm were at increased risk of influenza hospitalization up to age five. METHODS: National registry data on all children born in Norway between 2008 and 2011 were used in Cox regression models to estimate adjusted hazard ratios (aHRs) for influenza hospitalizations up to age five in children born preterm (<37 pregnancy weeks). HRs were also estimated separately for very preterm (<32 weeks), early term (37-38 weeks), and post-term (≥42 weeks) children. RESULTS: Among 238,628 children born in Norway from January 2008 to December 2011, 15,086 (6.3%) were born preterm. There were 754 (0.3%) children hospitalized with influenza before age five. The rate of hospitalizations in children born preterm was 13.8 per 10,000 person-years (95% confidence interval [CI] [11.3, 16.7]), and 5.9 per 10,000 person-years (95% CI [5.5, 6.4]) in children born at term (≥37 weeks). Children born preterm had a higher risk of influenza hospitalization before age 5: aHR 2.33 (95% CI [1.85, 2.93]). The risk increased with decreasing gestational age and was highest among those born extremely/very preterm; aHR 4.07 (95% CI [2.63, 6.31]). Compared with children born at 40-41 weeks, children born early term also had an elevated risk of influenza hospitalization; aHR (37 weeks) 1.89 (95% CI [1.43, 2.50]), aHR (38 weeks) 1.43 (95% CI [1.15, 1.78]). CONCLUSION: Children born preterm had a higher risk of influenza hospitalizations before age five. An elevated risk was also present among children born at an early term. Children born preterm could benefit from influenza vaccinations.

Clinical Outcome of Viral Respiratory Tract Infections in Hospitalized Adults in Norway: High Degree of Inflammation and Need of Emergency Care for Cases With Respiratory Syncytial Virus.

Background: The clinical features and outcomes of viral respiratory tract infections (RTIs) in adults have not been thoroughly studied, especially the respiratory syncytial virus (RSV) disease burden. It has become apparent that outbreaks of RSV in the elderly are associated with increased hospitalization rates. However, little data exists on the severity of such viral RTIs in adults, particularly the need for hospitalization, respiratory support and intensive care. Methods: We conducted a retrospective observational single-center study at Østfold Hospital Trust, Norway, during three winter seasons 2015-2018. Patients ≥18 years with either influenza A, influenza B, RSV A/B, human metapneumovirus, parainfluenza virus 1-4 or adenovirus detected in respiratory specimens were included, if they were hospitalized 14 days prior or following the detection date, with signs of RTI. Hospital records on treatment and outcome were investigated, as well as mortality of all causes up to 30 days from discharge. Results: Of the 1222 infection events that were included, influenza A was the most frequent virus detected (39%), while 179 infection events (14.6%) were due to RSV. Influenza B counted for 24% of the infection events, human metapneumovirus 13%, parainfluenza virus 9% and adenovirus 1%. Patients admitted with RSV more often suffered from COPD and congestive heart failure than patients with influenza A. In addition, RSV patients were overrepresented in the urgent response NEWS score (National Early Warning Score) category ≥5. RSV patients also showed signs of more severe inflammation, with WBC ≥11.1 × 109/L and CRP >100 mg/L, and they were more often treated with antibiotic agents during their hospital stay. However, we found no differences in the need for ICU admission or mortality. Conclusion: Patients with RSV had more often high values for markers of inflammation and elevated NEWS score when compared to patients hospitalized with other common respiratory viruses. Taken into account that they suffered more frequently from comorbidities like COPD, these patients needed hospitalization more urgently. These findings highlight the need for further investigations on RSV disease in adults and the elderly.

Visiting crowded places during the COVID-19 pandemic. A panel study among adult Norwegians.

Non-pharmaceutical interventions, including promotion of social distancing, have been applied extensively in managing the COVID-19 pandemic. Understanding cognitive and psychological factors regulating precautionary behavior is important for future management. The present study examines the importance of selected factors as predictors of having visited or intended to visit crowded places. Six online questionnaire-based waves of data collection were conducted in April-October 2020 in a Norwegian panel (≥18 years). Sample size at Wave 1 was 1,400. In the present study, "Visited or intended to visit crowded places" for different types of locations were the dependent variables. Predictors included the following categories of items: Perceived response effectiveness, Self-efficacy, Vulnerability, Facilitating factors and Barriers. Data were analyzed with frequency and percentage distributions, descriptives, correlations, principal components analysis, negative binomial-, binary logistic-, and multiple linear regression, and cross-lagged panel models. Analyses of dimensionality revealed that a distinction had to be made between Grocery stores, a location visited by most, and locations visited by few (e.g., "Pub," "Restaurants," "Sports event"). We merged the latter set of variables into a countscore denoted as "Crowded places." On the predictor side, 25 items were reduced to eight meanscores. Analyses of data from Wave 1 revealed a rather strong prediction of "Crowded places" and weaker associations with "Supermarket or other store for food." Across waves, in multiple negative binomial regression models, three meanscore predictors turned out to be consistently associated with "Crowded places." These include "Response effectiveness of individual action," "Self-efficacy with regard to avoiding people," and "Barriers." In a prospective cross-lagged model, a combined Response effectiveness and Self-efficacy score (Cognition) predicted behavior ("Visited or intended to visit crowded places") prospectively and vice versa. The results of this study suggest some potential to reduce people's visits to crowded locations during the pandemic through health education and behavior change approaches that focus on strengthening individuals' perceived response effectiveness and self-efficacy.