Coronaviruses of the human variety have been the culprit of global epidemics of varying levels of lethality, including COVID-19, which has impacted more than 200 countries and resulted in 5.7 million fatalities as of May 2022. Effective clinical management necessitates the allocation of sufficient resources and the employment of appropriately skilled personnel. The elderly population and individuals with diabetes are at increased risk of more severe manifestations of COVID-19. Countries with a higher gross domestic product (GDP) typically exhibit superior health outcomes and reduced mortality rates. Here, we suggest a predictive model for the density of medical doctors and nursing personnel for 134 countries using a support vector machine (SVM). The model was trained in 107 countries and tested in 27, with promising results shown by the kappa statistics and ROC analysis. The SVM model used for predictions showed promising results with a high level of agreement between actual and predicted cluster values.

This article proposes a continuous time mortality model based on calendar years. Mortality rates belong to a mean-reverting random field indexed by time and age. In order to explain the improvement of life expectancies, the reversion level of mortality rates is the product of a deterministic function of age and of a decreasing jump-diffusion process driving the evolution of longevity. We provide a general closed-form expression for survival probabilities and develop it when the mean reversion level of mortality rates is proportional to a Gompertz–Makeham law. We develop an econometric estimation method and validate the model on the Belgian population.

The purpose of this paper is to identify a workhorse mortality model for the adult age range (i.e., excluding the accident hump and younger ages). It applies the “general procedure” (GP) of Hunt & Blake [(2014), North American Actuarial Journal, 18, 116–138] to identify an age-period model that fits the data well before adding in a cohort effect that captures the residual year-of-birth effects arising in the original age-period model. The resulting model is intended to be suitable for a variety of populations, but economises on the number of period effects in comparison with a full implementation of the GP. We estimate the model using two different iterative maximum likelihood (ML) approaches – one Partial ML and the other Full ML – that avoid the need to specify identifiability constraints.

Infection caused by parasitic nematodes of humans and livestock can have significant health and economic costs. Treatments aimed at alleviating these costs, such as chemotherapy and vaccination, alter parasite survival and reproduction, the main selective pressures shaping life-history traits such as age to maturity, size and fecundity. Most authors have argued that the life-history evolution prompted by animal and public health programmes would be clinically beneficial, generating smaller, less fecund worms, and several mathematical models support this view. However, using mathematical models of long-lasting interventions, such as vaccination, and regularly repeated short interventions, such as drenching, we show here that the expected outcome actually depends on how mortality rates vary as a function of worm size and developmental status. Interventions which change mortality functions can exert selection pressure to either shorten or extend the time to maturity, and thus increase or decrease worm fecundity and size. The evolutionary trajectory depends critically on the details of the mortality functions with and without the intervention. Earlier optimism that health interventions would always prompt the evolution of smaller, less fecund and hence clinically less damaging worms is premature.

This Panel Session consisted of three country reports (Bagladesh, Bhutan, and Myanmar) and the common issues identified during the Panel discussions relative to water-related hazards and events in the Southeast Asia Region. The primary event discussed regardless of the hazards encountered was flooding. The merits of the responses generated in Bangladesh before, during, and following the 2004 floods provide evidence of what can be accomplished in community and national levels of preparedness.

Many key issues arose in the discussions: (1) command and control systems and SOPs; (2) ready resources; (3) public information and education and human resource development; (4) community-level preparedness; (5) accessibility to health care; (6) increased focus on disease prevention and control; (7) management of dead bodies; (8) need for a legal framework; (9) funding and the management of funds; and (10) relationships with themedia.

In this paper, I seek to delineate the build-up of the Italian slave population. My parametric model revolves around two variables: the probable number of slaves in Roman Italy, and the demographic structure of the servile population. I critique existing estimates of slave totals and propose a new ‘bottom-up’ approach; discuss the probable sex ratio, mortality regime and family structure of the Italian slaves; and advance a new estimate of the overall volume of slave transfers. I argue that the total number of slaves in Roman Italy did not exceed one-and-a-half million, and that this population had been created by the influx of between two and four million slaves during the last two centuries B.C.

Complex humanitarian emergencies lack a mechanism to coordinate, communicate, assess, and evaluate response and outcome for the major participants (United Nations, Intenational Committee of the Red Cross, non-governmental organizations and military forces). Success in these emergencies will depend on the ability to accomplish agreed upon measures of effectiveness (MOEs). A recent civil-military humanitarian exercise demonstrated the ability of participants to develop consensus-driven MOEs. These MOEs combined security measures utilized by the military with humanitarian indicators recognized by relief organizations. Measures of effectiveness have the potential to be a unifying disaster management tool and a partial solution to the communication and coordination problems inherent in these complex emergencies.