Impact of changes in protective behaviors and out-of-household activities by age on COVID-19 transmission and hospitalization in Chicago, Illinois

Agent-based simulation and child protection systems: Rationale, implementation, and verification

BACKGROUND AND OBJECTIVE

Simulation models are an important tool used in health care and other disciplines to support operational research and decision-making. In the child protection literature, simulation models are an under-utilized source of research evidence.

PARTICIPANTS AND SETTING

In this paper, we describe the rationale for and the development of an agent-based simulation of a child protection system in the US. Using the investigation, prevention service, and placement histories of 600,000 children served in an urban child welfare system, we walk the reader through the development of a prototype known as OSPEDALE.

METHODS

The governing equations built into OSPEDALE probabilistically simulate the onset of investigations. Then, drawing from empirical survival distributions, the governing equations trace the probability of subsequent interactions with the system (recurrence of maltreatment, service referrals, and placement) conditional on the characteristics of children, their assessed risk level, and prior child protection system involvement.

RESULTS

As an initial test of OSPEDALE's utility, we compare empirical admission counts with counts generated from OSPEDALE. Though the verification step is admittedly simple, the comparison shows that OSPEDALE replicates the empirical count of new admissions closely enough to justify further investment in OSPEDALE.

CONCLUSIONS

Management of public child protection systems is increasingly research evidence-dependent. The emphasis on research evidence as a decision-support tool has elevated evidence acquired through randomized clinical trials. Though important, the evidence from clinical trials represents only one type of research evidence. Properly specified, simulation models are another source of evidence with real-world relevance.

An agent-based secure privacy-preserving decentralized protocol for sharing and managing digital health passport information during crises

The aim of this article is to identify a range of changes and challenges that present-day technologies often present to contemporary societies, particularly in the context of smart city logistics, especially during crises. For example, the long-term consequences of the COVID-19 pandemic, such as life losses, economic damages, and privacy and security violations, demonstrate the extent to which the existing designs and deployments of technological means are inadequate. The article proposes a privacy-preserving, decentralized, secure protocol to safeguard individual boundaries and supply governments and public health organizations with cost-effective information, particularly regarding vaccination. The contribution of this article is threefold: (i) conducting a systematic review of most of the privacy-preserving apps and their protocols created during pandemics, and we found that most apps pose security and privacy violations. (ii) Proposing an agent-based, decentralized private set intersection (PSI) protocol for securely sharing individual digital personal and health passport information. The proposed scheme is called secure mobile digital passport agent (SMDPA). (iii) Providing a simulation measurement of the proposed protocol to assess performance. The performance result proves that SMDPA is a practical solution and better than the proposed active data bundles using secure multi-party computation (ADB-SMC), as the average CPU load for SMDPA is approximately 775 milliseconds (ms) compared to about 900 ms for ADB-SMC.