The Nordic Pandemic Preparedness Modelling Network monthly webinars

January 18th 2024, Norway

Estimating the household secondary attack rate with the Incomplete Chain Binomial model.

Jonas Christoffer Lindstrøm, Norwegian Institute of Public Health
 
We use the Chain Binomial model to estimate the Secondary Attack Rate in household studies. We extend the model to allow for inference in incompletely observed outbreaks, and illustrate the methodology on two data sets. We have also implemented an R package for the model.

February 29 2024, Sweden

Analysis of the boundary between as simple model as possible and too simple model in studies of outbreaks of new types of diseases.

Fredrik Liljeros, Department of Sociology, Stockholm University

(no abstract)

April 4 2024, Finland

Unifying incidence and prevalence under a time-varying general branching process

Mikko Pakkanen, Imperial College London

In epidemiology, renewal equations are a popular approach used in modelling the number of new infections, i.e., incidence, in an outbreak. We develop a stochastic model of an outbreak based on a time-varying variant of the Crump-Mode-Jagers branching process. This model accommodates a time-varying reproduction number and a time-varying distribution for the generation interval. We then derive renewal-like integral equations for incidence, cumulative incidence and prevalence under this model. We also investigate some of the salient theoretical properties of these equations. Finally, we present a numerical discretisation scheme to solve the equations and use this scheme to estimate rates of transmission from serological prevalence of SARS-CoV-2 in the UK and historical incidence data on Influenza, Measles, SARS and Smallpox. Joint work with X. Miscouridou, M. J. Penn, C. Whittaker, T. Berah, S. Mishra, T. A. Mellan and S. Bhatt.

May 2024

(replaced by workshop in Denmark)

12 September 2024, Denmark

Robust estimation of seasonal onset and intensity of viral respiratory infections

Sofia Myrup Otero, Data Scientist at SSI

The aim of this study is to develop a more robust alternative to the Moving Epidemic Method (MEM), which is commonly used in the surveillance of viral respiratory viruses.
The MEM has shown to be overly sensitive to fluctuations between seasons and relies on an arbitrary parameter, making it difficult to interpret, compare and apply consistently.
Therefore, we propose an alternative method that utilizes timely detection of seasonal onset and adaptive calculations of intensity levels.

Waning of multiple outcomes in ODE compartmental models

Rasmus Skytte Randløv, PhD, Special Consultant at SSI

Inspired by Mohamed El Khalifi and Tom Brittons work on extending SIRS models with gradual waning of immunity, we implement generalized numerical methods to account for waning of multiple outcomes in ODE compartmental models. Notably, our extension allows for simultaneous waning of immunity against infection and against hospitalization when these wane at different time scales.

10 October 2024, Finland

Vaccine effectiveness and herd immunity for HPV16 in partly open population

Simopekka Vänskä, senior researcher, THL

Often the predictions of vaccine effectiveness are estimated by models with a closed population. In this talk, considering HPV16, the openness of population is included the analysis. We show how the openness is implemented for the sexual contact structure through which HPV (human papillomavirus) transmits, and how the level of openness changes the vaccine effectiveness, depending on the vaccination strategy (girls-only, or boys-and-girls vaccination).

7 Novembre 2024, Norway

Contact Tracing in ABMs

Ida-Marie Fauske Johansson

The COVID-19 contact tracing data from Oslo municipality provides valuable insights into the contact patterns among various age groups and districts within the city. Utilizing this data, we developed an agent-based model to simulate the first two years of the COVID-19 pandemic. Our goal is to evaluate the effectiveness of the contact tracing strategy in Oslo. In this presentation, I will introduce our agent-based model, outline the key assumptions underlying our simulations, and discuss how we will proceed with model calibration and scenario analysis.

A modelling study of hepatitis C infection among people who inject drugs and immigrants

Jørgen Eriksson Midtbø

The global incidence target for the elimination of hepatitis C among people who inject drugs (PWID) is <2/100. In Norway, the hepatitis C epidemic is concentrated in PWID. Immigrants are the second most important risk group for chronic infection. Using a stochastic compartmental model, we estimated the incidence of hepatitis C among active PWID, and the prevalence of chronic infection among active PWID, ex-PWID, and immigrants in Norway up to 2022. I will present the model and discuss some of the particular challenges we faced, including a non-constant size of the PWID population over time. The work is published in The Journal of Infectious Diseases: https://doi.org/10.1093/infdis/jiae147

5 December 2024, Sweden

Modeling of Vector-Borne Diseases accounting for Climate Chang

• Jonas Wallin, Lund University

A significant concern in Europe due to potential climate change is the introduction of new vectors, particularly mosquitoes. This development can lead to the emergence of diseases previously considered tropical, such as Dengue fever and West Nile virus. In this talk, I will present recent projects involving the statistical modeling of vector-borne diseases.

The primary applications are generating scenarios under climate change (long-term forecasting) and developing early warning systems (filtering or just-in-time prediction). To model the vectors, we have utilized two main classes of models: mechanistic process-based models and data-driven models. I will discuss the limitations of these approaches and suggest possible extensions to enhance state-of-the-art modeling for both filtering and long-term forecasting.

6 February 2025, Denmark

Which fecal indicator to use for normalizing SARS-CoV-2 concentrations in wastewater

Lasse Engbo Christiansen, Senior Research, Statens Serum Institut

SARS-CoV-2 concentration multiplied by flow provides a simple estimate of the amount of virus that is excreted in a catchment. However, rainfall, infiltration, and water from industries are diluting the fecal matter that is flushed from toilets. PMMoV is commonly used as a fecal indicator but it shows seasonal variation so we are testing three alternatives. This gives rise to even more questions and thus analysis where I will present the current state.

Wastewater informs hospital admissions

Lasse Engbo Christiansen, Senior Research, Statens Serum Institut

The reporting of admissions with and due to COVID-19 is delayed. Nowcasting and forecasting can improve the information but SARS-CoV-2 concentrations in wastewater can improve it even further.

6 March 2025, Finland

Communicating Deaths: Different Mortality Metrics

Simopekka Vänskä, senior researcher, THL

(no abstract)

3 April 2025, bonus

The Politics of the Pandemic in Eastern Europe and Eurasia - Blame Game and Governance

M. Zavadskaya, Finnish Institute of International Affairs (FIIA) and researcher at the Aleksanteri Institute, University of Helsinki

• The Politics of the Pandemic in Eastern Europe and Eurasia (www.routledge.com)

This talk provides a comprehensive overview of the political impact of the COVID-19 emergency in central and eastern Europe and Eurasia. Offering a theoretical framework linking the authoritarian, post-Soviet institutional legacy with patterns of political behavior, support and governments’ policies, the expert contributors argue that domestic political regimes mediate and shape citizens’ perceptions of public health crises, and the very regimes’ political survival. The authors explore how the pandemic affected regime change, government stability, business groups and civil societies in more than 15 countries of the region from the discovery of the virus to the vaccination rollout. The studies rely on a broad range of empirical evidence from the region – survey, state statistics, ethnography and interviews.

Formulating, explaining and empirically testing the causal mechanisms that drive political accountability and support through a cross-country comparison and in-depth case studies of popular and electoral support attempting to highlight any patterns specific to the region, this book contributes to studies of governance and political accountability in low-trust countries with authoritarian legacies and proclivities. Drawing on an interdisciplinary approach that brings together area studies, history, sociology and political science, it will also be of value to those interested in systematic effect of political regimes on handling public health crises.

8 May 2025, Sweden

Identifiability in an epidemic model with prior immunity and under-reporting

Fanny Bergström, Stockholm U

Abstract: We examine the identifiability of a modified SIR model that accounts for under-reporting and pre-existing immunity in the population. We provide a mathematical proof of the unidentifiability and later show that we are able to identify the model parameters using properties of the deterministic SIR model and survey data of either the prior immunity or under-reporting. Our results show the limitations of parameter inference in partially observed epidemics and the importance of identifiability analysis in the development and application of models for public health decision-making.

Sideward Contact Tracing in an Epidemic Model with Mixing Groups

Dongni Zhang, LInköping U

Abstract: We consider a stochastic epidemic model with sideward contact tracing, where infection occurs through interactions at gatherings involving two or more individuals (referred to as mixing events). In contrast to traditional tracing methods, which focus on identifying the infector or the infectees of an index case, sideward tracing targets those infected during the same event. The early stage of the epidemic is analysed using a branching process with sibling dependencies. To address the challenges given by the dependencies, we aggregate sibling groups (individuals who become infected at the same event) into macro-individuals and define a corresponding macro-branching process. This approach allows us to derive an expression for the effective macro-reproduction number, which is equivalent to the effective individual reproduction number, and serves as a threshold for the behaviour of the epidemic. Our numerical examples reveal that sideward tracing can substantially reduce the reproductive number, particularly when mixing events are larger or when super-spreading events occur. However, we also highlight its limitations: without restrictions on gathering size, the reproductive number may remain excessively high, making it infeasible to reduce it below one even with perfect tracing. These findings underscore the potential and the challenges of sideward tracing as a control measure, especially in scenarios where gathering size limitations are relaxed.

• Sideward Contact Tracing in an Epidemic Model with Mixing Groups (link.springer.com)