Modeling the effect of time delay in the increment of number of hospital beds to control an infectious disease

Analysing monkeypox epidemic drivers: Policy simulation and multi-index modelling across 39 nations

Background

This study aimed to analyse the drivers of the monkeypox (Mpox) epidemic and policy simulation to support health care policies against the Mpox epidemic.

Methods

We established a three-round selection mechanism for 164 factors using Lasso and negative binomial regression to investigate the correlation between significant drivers and the cumulative confirmed cases of Mpox. Policy simulation for each driver was evaluated, and the varying effects of implementation at different times were examined.

Results

HIV/AIDS prevalence and air transport passengers carried were significant determinants of the risk of the Mpox epidemic across various countries, with regression coefficients of 1.417 and 0.766, respectively. A decrease in HIV/AIDS prevalence by 10, 20, 30, and 40% corresponded to reductions in the number of Mpox cases by 6.28, 6.55, 6.87, and 7.26%, respectively. Similarly, 20, 40, 60, and 80% travel restrictions led to reductions in Mpox cases by 7.16, 15.63, 26.28%, and 41.46%, respectively. Controlling air transport passengers carried in the first month could postpone outbreak onset by 0.5-2.0 months.

Conclusions

Mpox prevention and control policies should primarily focus on travel restrictions during high disease-risk periods and flight suspensions from high-risk nations in combination with regular HIV/AIDS prevention and treatment strategies.

Modeling the impact of hospital beds and vaccination on the dynamics of an infectious disease

The unprecedented scale and rapidity of dissemination of re-emerging and emerging infectious diseases impose new challenges for regulators and health authorities. To curb the dispersal of such diseases, proper management of healthcare facilities and vaccines are core drivers. In the present work, we assess the unified impact of healthcare facilities and vaccination on the control of an infectious disease by formulating a mathematical model. To formulate the model for any region, we consider four classes of human population; namely, susceptible, infected, hospitalized, and vaccinated. It is assumed that the increment in number of beds in hospitals is continuously made in proportion to the number of infected individuals. To ensure the occurrence of transcritical, saddle-node and Hopf bifurcations, the conditions are derived. The normal form is obtained to show the existence of Bogdanov-Takens bifurcation. To validate the analytically obtained results, we have conducted some numerical simulations. These results will be useful to public health authorities for planning appropriate health care resources and vaccination programs to diminish prevalence of infectious diseases.

Allocation of hospital beds on the emergence of new infectious disease: A mathematical model

This paper is concerned to a mathematical model for the management of hospital beds when a new infection emerges in the population with the existing infections. The study of this joint dynamics presents formidable mathematical challenges due to a limited number of hospital beds. We have derived the invasion reproduction number, which investigates the potential of a newly emerged infectious disease to persist when some infectious diseases are already invaded the host population. We have shown that the proposed system exhibits transcritical, saddle-node, Hopf, and Bogdanov-Takens bifurcations under certain conditions. We have also shown that the total number of infected individuals may increase if the fraction of the total number of hospital beds is not properly allotted to the existing and a newly emerged infectious disease. The analytically obtained results are verified with the help of numerical simulations.