Moritz Kersting’s research while affiliated with University of Göttingen and other places

Mobility and transportation service requirements change with growing age. Also in a car-based society like Germany many seniors need to give up driving the car and are dependent on relatives or public transport. Especially in rural areas, the accessibility of public transport is often limited. Demand responsive transportation has occasionally been proposed by researchers as a viable alternative to stop-, route- and time-based public transportation to address such problems. This case study analyses passenger data from the true DRT system EcoBus to identify distinct drivers of old passengers’ satisfaction compared to other passengers. Contrary to existing literature, older people stated to be even more satisfied with the service then younger travellers did. Moreover, older travellers tend to travel alone, but showed slightly higher satisfaction when travelling in groups. The results suggest that older people might be more open-minded and positive regarding flexible public transport schemes than expected.

Everyday commuting as a mobility phenomenon is well-investigated and has been the topic of many contributions. Nevertheless, the distinct determinants of the commuting professional’s motivation to regularly travel comparably long distances have not been in the focus of research yet. Thus, this contribution analyses the sociodemographic variables that underpin the well-educated group’s decision to commute longer distances than other educational groups. For German Microcensus data, ordered logistic regression models are used to estimate and compare the influences of sociodemographic variables on all commuting employees and commuting professionals. The data of German Microcensus of the year 2012 are used for the analysis. The results imply that some characteristics exert the already known effects on both samples. Others do vary with education and thus illustrate some unique sociodemographic influences on the commuting behaviour of professionals.

COVID-19 has spread rapidly around the globe. While there has been a slow down of the spread in some countries, e.g., in China, the African continent is still at the beginning of a potentially wide spread of the virus. Owing to its economic strength and imbalances, South Africa is of particular relevance with regard to the drastic measures to prevent the spread of this novel coronavirus. In March 2020, South Africa imposed one of the most severe lockdowns worldwide and subsequently faced the number of infections slowing down considerably. In May 2020, this lockdown was partially relaxed and further easing of restrictions was envisaged. In July and August 2020, daily new infections peaked and declined subsequently. Lockdown measures were further relaxed. This study aims to assess the recent and upcoming measures from an epidemiological perspective. Agent-based epidemic simulations are used to depict the effects of policy measures on the further course of this epidemic. The results indicate that measures that are either lifted too early or are too lenient have no sufficient mitigating effects on infection rates. Consequently, continuous exponential infection growth rates or a second significant peak of infected people occur. These outcomes are likely to cause higher mortality rates once healthcare capacities are occupied and no longer capable to treat all severely and critically infected COVID-19 patients. In contrast, strict measures appear to be a suitable way to contain the virus. The simulations imply that the initial lockdown of 27 March 2020 was probably sufficient to slow the growth in the number of infections, but relaxing countermeasures might allow for a second severe outbreak of COVID-19 in our investigated simulation region of Nelson Mandela Bay Municipality.

Tuberculosis (TB) is the 10th leading cause of death worldwide, and since 2007 it has been the main cause of death from a single infectious agent, ranking above HIV/AIDS. The current COVID-19 is a pandemic which caused many deaths around the world. The danger is not only a coinfection as observed for TB and HIV for a long time, but that both TB and SARS-CoV-2 affect the respiratory organs and thus potentiate their effect or accelerate the critical course. A key public health priority during the emergence of a novel pathogen is the estimation of the clinical need to assure adequate medical treatment. This requires a correct adjustment to the critical case detection rate and the prediction of possible scenarios based on known patterns. The African continent faces constraining preconditions in regard to healthcare capacities and social welfare which may hinder required countermeasures. However, given the high TB prevalence rates, COVID-19 may show a particular severe course in respective African countries, e.g. South Africa. Using WHO's TB and public infrastructure data, we conservatively estimate that the symptomatic critical case rate, which affects the healthcare system, is between 8 and 12% due to the interaction of COVID-19 and TB, for a TB population of 0.52% in South Africa. This TB prevalence leads to a significant increase in the peak load of critical cases of COVID-19 patients and potentially exceeds current healthcare capacities.

The future dynamics of the Corona Virus Disease 2019 (COVID-19) outbreak in African countries is largely unclear. Simultaneously, required strengths of intervention measures are strongly debated because containing COVID-19 in favor of the weak health care system largely conflicts with socio-economic hardships. Here we analyze the impact of interventions on outbreak dynamics for South Africa, exhibiting the largest case numbers across sub-saharan Africa, before and after their national lockdown. Past data indicate strongly reduced but still supracritical growth after lockdown. Moreover, large-scale agent-based simulations given different future scenarios for the Nelson Mandela Bay Municipality with 1.14 million inhabitants, based on detailed activity and mobility survey data of about 10% of the population, similarly suggest that current containment may be insufficient to not overload local intensive care capacity. Yet, enduring, slightly stronger or more specific interventions, combined with sufficient compliance, may constitute a viable option for interventions for South Africa.

Background: COVID-19 has spread from China across Europe and the United States and has become a global pandemic. In countries of the Global South, due to often weaker socioeconomic options and health care systems, effective local countermeasures remain debated. Methods: We combine large-scale socioeconomic and traffic survey data with detailed agent-based simulations of local transportation to analyze COVID-19 spreading in a regional model for the Nelson Mandela Bay Municipality in South Africa under a range of countermeasure scenarios. Results: The simulations indicate that any realistic containment strategy, including those similar to the one ongoing in South Africa, may yield a manifold overload of available intensive care units. Only immediate and the most severe countermeasures, up to a complete lock-down that essentially inhibits all joint human activities, can contain the epidemic effectively. Conclusions: As South Africa exhibits rather favorable conditions compared to many other countries of the Global South, our findings constitute rough conservative estimates and may support identifying strategies towards containing COVID-19 as well as any major future pandemics in these countries.

Disruptive developments in automated driving systems, new powertrain concepts and digital mobility are shaping changes in the way people move in rural and urban areas. In combination with these technical potentials, novel mobility concepts as for instance demand responsive transportation (DRT) can improve the everyday mobility of people in terms of both cost-efficiency and sustainability. Moreover, challenges related to demographic transitions and urbanisation can be addressed and negative developments mitigated. One potential application of DRT might be the connection of rural areas with the urban core. The following paper aims to evaluate the viability and feasibility of DRT systems in the interplay of rural and urban areas. The city of Bremerhaven and the immediate surrounding are selected as area of investigation and the agent-based modelling framework MATSim is used to simulate the inhabitant mobility behaviour. On this basis, the global operational costs are calculated for different scenarios, e.g. fully automated vehicles and various powertrain types. The results imply that automated DRT systems are applicable to reduce the economic and environmental costs of transportation when applied in the interplay of rural and urban areas.

The future dynamics of the Corona Virus Disease 2019 (COVID-19) outbreak in Africa is largely unclear. Simultaneously, required strengths of intervention measures are strongly debated because containing COVID-19 in favor of the weak health care system largely conflicts with socio-economic hardships. Here we analyze the impact of interventions on outbreak dynamics for South Africa, exhibiting the largest case numbers across Sub-Saharan Africa, before and after their national lockdown. Past data indicate strongly reduced but still supracritical growth after lockdown. Agent-based simulations of different future scenarios for the Nelson Mandela Bay Municipality with 1.14 million inhabitants, based on detailed activity and mobility survey data of about 10\% of the population, similarly suggest that current containment may be insufficient to not overload local intensive care capacity. Yet, enduring, slightly stronger or more specific interventions, combined with sufficient compliance may constitute a viable option for interventions for South Africa and potentially many regions in Africa and the Global South. See also extended version on medRxiv.org https://doi.org/10.1101/2020.04.24.20077891

One Sentence Summary: Regional agent-based scenario simulations of the COVID-19 outbreak in South Africa suggest that countermeasures in many countries of the Global South are required to be especially rapid and severe to not overload the capacity set by locally available intensive care units.

COVID-19 has spread from China across Europe and the United States and has become a global pandemic. In countries of the Global South, due to often weaker socioeconomic options and health care systems, effective local countermeasures remain debated. We combine large-scale socioeconomic and traffic survey data with detailed agent-based simulations of local transportation to analyze COVID-19 spreading in a regional model for the Nelson Mandela Bay Municipality in South Africa under a range of countermeasure scenarios. The simulations indicate that any realistic containment strategy, including those similar to the one ongoing in South Africa, may yield a manifold overload of available intensive care units (ICUs). Only immediate and the most severe countermeasures, up to a complete lock-down that essentially inhibits all joint human activities, can contain the epidemic effectively. As South Africa exhibits rather favorable conditions compared to many other countries of the Global South, our findings constitute rough conservative estimates and may support identifying strategies towards containing COVID-19 as well as any major future pandemics in these countries.