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

BackgroundDuring 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. MethodsWe conducted an online survey among a nationally representative sample of Norwegian adults, including six data collections/waves between April and September 2020, and used survey data from 2017 as baseline. We calculated mean daily contacts, and estimated age-stratified contact matrices that were used to estimate reproduction numbers during the study period. ResultsThe mean daily number of contacts varied between 3.2 (95% CI 3.0-3.4) to 3.9 (95% CI 3.6-4.2) across waves, representing a 67-73% decline compared to pre-pandemic levels. 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, 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. ConclusionSocial contacts experienced a significant decline during the months following the March 2020 lockdown in Norway, aligning with the implementation of stringent social distancing measures. The findings contribute valuable empirical information into the social behaviour of the Norwegian population during the early pandemic, which can be used to enhance policy-relevant models for addressing future crises when mitigation measures might be implemented.

Modeling geographic vaccination strategies for COVID-19 in Norway (preprint)

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.

Effects of Non-Compulsory and Mandatory COVID-19 Interventions on Travel Distance and Time Away from Home: The Case of Norway in 2021 (preprint)

Background: Due to the societal, economic, and health costs of COVID-19 non-pharmaceutical interventions (NPIs), it is important to assess their effects. Human mobility serves as a surrogate for human contacts and compliance to NPIs. In Nordic countries, NPIs have mostly been advised and sometimes made mandatory. It is unclear if making NPIs mandatory further reduced mobility. Aim: We 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. Methods: We 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 NPIs on mobility. Results: Nationally and in less populated regions, follow-up mandatory measures further decreased time, but not distance travelled. In urban areas, however, follow-up mandates also decreased distance, and the effect exceeded that of initial non-compulsory measures. Stricter metre rules, gyms closing and reopening, restrictions on guests in homes, and face mask recommendations most impacted distance travelled. Time travelled was most affected by gyms closing and restaurants and shops reopening. Conclusion: Overall, non-compulsory measures appeared to decrease distance travelled from home, while mandates further decreased this metric in urban areas. Time travelled is reduced more by mandates than by non-compulsory measures for all regions and interventions. Stricter distancing and restricted number of guests were associated with decreases in mobility.

Increased household transmission and immune escape of the SARS-CoV-2 Omicron variant compared to the Delta variant: evidence from Norwegian contact tracing and vaccination data (preprint)

We compared the secondary attack rate (SAR) of the SARS-CoV-2 Omicron and Delta variants in households using contact tracing data. Omicron SAR was higher (41%) than Delta (35%), likely due to immune evasion. Booster dose reduces risk of infection but has limited effect on preventing Omicron transmission.

A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the Covid-19 case (preprint)

During the first months, the Covid-19 pandemic has required most countries to implement complex sequences of non-pharmaceutical interventions, with the aim of controlling the transmission of the virus in the population. To be able to take rapid decisions, a detailed understanding of the current situation is necessary. Estimates of time-varying, instantaneous reproduction numbers represent a way to quantify the viral transmission in real time. They are often defined through a mathematical compartmental model of the epidemic, like a stochastic SEIR model, whose parameters must be estimated from multiple time series of epidemiological data. Because of very high dimensional parameter spaces (partly due to the stochasticity in the spread models) and incomplete and delayed data, inference is very challenging. We propose a state space formalisation of the model and a sequential Monte Carlo approach which allow to estimate a daily-varying reproduction number for the Covid-19 epidemic in Norway with sufficient precision, on the basis of daily hospitalisation and positive test incidences. The method is in regular use in Norway and is a powerful instrument for epidemic monitoring and management.

Regional probabilistic situational awareness and forecasting of COVID-19 (preprint)

Mathematical models and statistical inference are fundamental for surveillance and control of the COVID-19 pandemic. Several aspects cause regional heterogeneity in disease spread. Individual behaviour, mobility, viral variants and transmission vary locally, temporally and with the season, and interventions and vaccination are often implemented regionally. Therefore, we developed a new regional changepoint stochastic SEIR metapopulation model. The model is informed by real-time mobility estimates from mobile phone data, laboratory-confirmed cases, and hospitalisation incidence. To estimate locally and time-varying transmissibility, case detection probabilities, and missed imported cases, we present a new 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, suitable for real-time surveillance. By comparing the reproduction number before and after lockdown, we find a national transmissibility reduction of 85% (95% CI 78%-89%). The estimated effect varied regionally and was larger for the most populated regions than in the national average.

Assessment of COVID-19 intervention strategies in the Nordic countries using genomic epidemiology (preprint)

The Nordic countries, defined here as Norway, Sweden, Denmark, Finland and Iceland, are known for their comparable demographics and political systems. Since these countries implemented different COVID-19 intervention strategies, they provide a natural laboratory for examining how COVID-19 policies and mitigation strategies affected the propagation, evolution and spread of the SARS-CoV-2 virus. We explored how the duration, the size and number of transmission clusters, defined as country-specific monophyletic groups in a SARS-CoV-2 phylogenetic tree, differed between the Nordic countries. We found that Sweden had the largest number of COVID-19 transmission clusters followed by Denmark, Norway, Finland and Iceland. Moreover, Sweden and Denmark had the largest, and most enduring, transmission clusters followed by Norway, Finland and Iceland. In addition, there was a significant positive association between transmission cluster size and duration, suggesting that the size of transmission clusters could be reduced by rapid and effective contact tracing. Thus, these data indicate that to reduce the general burden of COVID-19 there should be a focus on limiting dense gatherings and their subsequent contacts to keep the number, size and duration of transmission clusters to a minimum. Our results further suggest that although geographical connectivity, population density and openness influence the spread and the size of SARS-CoV-2 transmission clusters, country-specific intervention strategies had the largest single impact.

Increased transmissibility of the B.1.1.7 SARS-CoV-2 variant: Evidence from contact tracing data in Oslo, January to February 2021 (preprint)

We use data from contact tracing in Oslo, Norway, to estimate the relative transmissibility of the new SARS-CoV-2 lineage B.1.1.7. Within households, we find an increase in the secondary attack rate by 60% (20% 114%) compared to other variants. In general, we find a significant increase in the estimated reproduction number of 24% (95% CI 0% - 52%), or an absolute increase of 0.19 compared to other variants.

The impact of early public health interventions on SARS-CoV-2 transmission and evolution (preprint)

Many countries have attempted to control COVID-19 through the implementation of non-pharmaceutical interventions. However, it remains unclear how different control strategies have impacted SARS-CoV-2 virus transmission dynamics at the local level. Using complete SARS-CoV-2 genomes, we inferred the relative frequencies of virus importation and exportation, as well as virus transmission chain dynamics in Nordic countries - Denmark, Finland, Iceland, Norway and Sweden - during the first months of the pandemic. Our analyses revealed that Sweden experienced more numerous transmission chains, which tended to have more cases, and were of longer duration, a set of features that increased with time. Together with Denmark, Sweden was also a net exporter of SARS-CoV-2. Hence, Sweden effectively constituted an epidemiological and evolutionary refugia that enabled the virus to maintain active transmission and spread to other geographic localities. This analysis highlights the utility of genomic surveillance where active transmission chain monitoring is a key metric.