Sterchi, Martin
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Sterchi, Martin
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- PublikationCovid-19 superspreading. lessons from simulations on an empirical contact network(2021) Hilfiker, Lorenz; Sterchi, MartinInfectious individuals who cause an extraordinarily large number of secondary infections are colloquially referred to as superspreaders. Their pivotal role for the transmission of Covid-19 has been exemplified by now infamous cases such as the Washington choir practice, where one infectious individual caused 52 secondary infections [1]. In order to formally analyse superspreading, we denote by Z the individual reproduction number. In a fully susceptible population, the mean mZ is known as the basic reproduction number R0. Based on branching arguments and assuming a well-mixed population, the distribution of Z is typically modelled by a negative binomial distribution whose variance mZ(1+mZ=kZ) is characterised by the dispersion parameter kZ [2]. Empirical evidence suggests that Covid-19 exhibits a particularly wide distribution of Z, with the right tail representing superspreading events. In situations without interventions, the dispersion parameter kZ was estimated in the range 0.04 - 0.2 [3, 4]. Some studies even found evidence for a fat tailed Z-distribution, possibly a power law with the exponent close to 1 [5, 6]. The underlying mechanisms for the emergence of this level of heterogeneity are difficult to establish. A priori, network effects could play a role, as suggested in [5]. A more frequent line of reasoning focuses on physiological or biological factors: wet pronunciation, loud speech, frequent coughing or higher viral loads could result in some infected individuals being inherently more prone to spread the disease than others during an encounter with a susceptible individual [7]. Combining both lines of thought, the study in [8] shows that individual variation in infectiousness indeed leads to higher variance of Z on some standard static network models. However, no previous study has investigated heterogeneities of the Z-distribution on empirical contact networks. Therefore, we provide preliminary simulation results based on one realistic temporal social contact network and gather further evidence that the key to finding Z-distributions in alignment with empirical data is to allow for individual variation in infectiousness.06 - Präsentation
- PublikationMeteoSwiss CHAPo: pollen information needs analysis(Fachhochschule Nordwestschweiz FHNW, 2021) Fuduric, Nikolina; Kraft, Corin; Sterchi, MartinThere is a network of pollen measurement devices in 14 stations throughout Switzerland. To date, the standard of pollen identification and measurement has been done manually with calculations and models providing forecasts with a six day delay. This standard is not serving the allergic public, the doctors and scientists specializing in pollen research any longer. A laser technology measurement device has successfully been tested in the regional center of MeteoSwiss in Payerne. It opens up new perspectives in terms of automation, real-time transmission and higher data quality. The technology is not only applicable to pollen measurement, but also enables partnerships to be strengthened in the areas of air quality and health effects. Based on this technology, MeteoSwiss can provide new, more valuable data products and services. With these new possibilities, two questions arise which are explored in this research report: Q1) What data products and services best serve the allergic public and doctors? Q2) Within which channels should these products be offered? MeteoSwiss has invited the University of Applied Sciences Northwestern Switzerland's (FHNW) School of Business to conduct a needs analysis of the two above-mentioned target groups. The needs analysis was carried out using a customer insights research-based method called “Jobs to Be Done” (JtbD) originally from Harvard University (Christensen 1997). The FHNW researchers extrapolated those jobs or tasks that were important to the target groups but not satisfied in the market. Upon isolating these “jobs”, MeteoSwiss experts from the CHAPo project and aha! were invited to design workshops at the FHNW to create a rough prototype of data products based on the research outcomes.05 - Forschungs- oder Arbeitsbericht
- PublikationMaximizing the likelihood of detecting outbreaks in temporal networks(Springer, 2020) Sterchi, Martin; Sarasua, Cristina; Grütter, Rolf; Bernstein, Abraham; Cherifi, Hocine; Gaito, Sabrina; Mendes, José Fernendo; Moro, Esteban; Rocha, Luis Mateus [in: Complex networks and their applications VIII. Volume 2 proceedings of the eighth international conference on complex networks and their applications. Complex Networks 2019]Epidemic spreading occurs among animals, humans, or computers and causes substantial societal, personal, or economic losses if left undetected. Based on known temporal contact networks, we propose an outbreak detection method that identifies a small set of nodes such that the likelihood of detecting recent outbreaks is maximal. The two-step procedure involves (i) simulating spreading scenarios from all possible seed configurations and (ii) greedily selecting nodes for monitoring in order to maximize the detection likelihood. We find that the detection likelihood is a submodular set function for which it has been proven that greedy optimization attains at least 63% of the optimal (intractable) solution. The results show that the proposed method detects more outbreaks than benchmark methods suggested recently and is robust against badly chosen parameters. In addition, our method can be used for outbreak source detection. A limitation of this method is its heavy use of computational resources. However, for large graphs the method could be easily parallelized.04B - Beitrag Konferenzschrift
- PublikationUnreliable is better: theoretical and practical impulses for performance management(Nomos, 2019) Stöckli, Sabrina; Messner, Claude; Sterchi, Martin; Dorn, Michael [in: Die Unternehmung]This review aims to stimulate discussion about a comprehensive understanding of performance evaluation – namely, the taken-for granted benefit of maximal reliable performance evaluation, where employee performance is evaluated with high levels of reliability (i.e., large samples of performance observations). So far, the management discipline has ignored the evidence-based view that one’s performance is better under unreliable performance evaluation compared to reliable performance evaluation. Drawing on tournament theory, behavioral research, and real-world sports data, we argue that while reliable performance evaluation boosts only superior employees, unreliable performance evaluation boosts all employees. The mechanisms that drive inferior and superior employees to perform better when evaluated unreliably substantiate that psychological insight is essential for efficient performance management. Overall, we complement the predominant thinking of performance management by offering innovative insights and implications that are significant for academics, employees, and employers.01B - Beitrag in Magazin oder Zeitung
- PublikationPig data. Transdisciplinary approach for health analytics of the Swiss Swine Industry(2018) Sterchi, MartinCombining big data methods and transdisciplinary approaches for providing sustainable solutions for real-time decision making in the Swiss Swine Industry.06 - Präsentation
