Mathematical model for COVID-19 management in crowded settlements and high-activity areas

COVID-19 transmission dynamics and the impact of vaccination: modelling, analysis and simulations

Despite the lifting of COVID-19 restrictions, the COVID-19 pandemic and its effects remain a global challenge including the sub-Saharan Africa (SSA) region. Knowledge of the COVID-19 dynamics and its potential trends amidst variations in COVID-19 vaccine coverage is therefore crucial for policy makers in the SSA region where vaccine uptake is generally lower than in high-income countries. Using a compartmental epidemiological model, this study aims to forecast the potential COVID-19 trends and determine how long a wave could be, taking into consideration the current vaccination rates. The model is calibrated using South African reported data for the first four waves of COVID-19, and the data for the fifth wave are used to test the validity of the model forecast. The model is qualitatively analysed by determining equilibria and their stability, calculating the basic reproduction number R0 and investigating the local and global sensitivity analysis with respect to R0. The impact of vaccination and control interventions are investigated via a series of numerical simulations. Based on the fitted data and simulations, we observed that massive vaccination would only be beneficial (deaths averting) if a highly effective vaccine is used, particularly in combination with non-pharmaceutical interventions. Furthermore, our forecasts demonstrate that increased vaccination coverage in SSA increases population immunity leading to low daily infection numbers in potential future waves. Our findings could be helpful in guiding policy makers and governments in designing vaccination strategies and the implementation of other COVID-19 mitigation strategies.

Global dynamics of a diffusive SIR epidemic model with saturated incidence rate and discontinuous treatments

In this paper, we study a diffusive SIR epidemic model with saturated incidence rate and discontinuous treatments under Neumann boundary conditions. Firstly, the existence and boundedness of the solution of the system are addressed. Then, on the basis of the differential inclusions theory, we analysis the existence of endemic equilibrium. Furthermore, by constructing different appropriate Lyapunov functions, we investigate the global asymptotic stability of the disease free equilibrium(DFE) and the endemic equilibrium(EE), respectively. Additionally, numerical simulations are given to confirm the correctness of theorem. Finally, we give a brief conclusion and discussion in the end of the paper.

Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several challenges including data availability and quality, the applicability of existing models to those contexts, the accurate modelling of cultural differences or specificities of those operational settings, the communication of results and uncertainties, as well as the alignment of strategic goals between diverse partners in complex situations. In this paper, we systematically review the limited epidemiological modelling work applied to refugee and IDP settlements so far, and discuss challenges and identify lessons learnt from the process. With the likelihood of disease outbreaks expected to increase in the future as more people are displaced due to conflict and climate change, we call for the development of more approaches and models specifically designed to include the unique features and populations of refugee and IDP settlements. To strengthen collaboration between the modelling and the humanitarian public health communities, we propose a roadmap to encourage the development of systems and frameworks to share needs, build tools and coordinate responses in an efficient and scalable manner, both for this pandemic and for future outbreaks.

Acute respiratory infections in an adult refugee population: an observational study

The presence of acute infectious respiratory diseases (ARD) is one of the main reasons why recently arrived refugees seek medical help. This paper investigates the incidence rates of acute respiratory diseases in an adult refugee population as well as associated sociodemographic factors and drug treatments. We conducted a retrospective observational study of deidentified medical records. The data were collected between 2015 and 2019 in the health care centers of two large German initial reception centers for refugees. Multivariable analyses controlling for sociodemographics were carried out using generalized estimating equations. Out of 10,431 eligible residents, 6965 medical encounters of 2840 adult patients were recorded over 30 months. Of all the adult patients, 34.4% sought medical help for a respiratory symptom or diagnosis at least once. Older patients and patients from Sub-Saharan Africa sought help less often. The occurrence of ARD showed a typical distribution over the course of the year. Facility occupancy was not associated with ARD occurrence. Acute respiratory symptoms are a leading cause for adult refugee patients to seek medical care. The doctor contact rates due to ARD were consistently two to three times higher among refugees than among German residents.