Equity in genetic newborn screening

State‐level newborn screening allows for early treatment of genetic disorders, which can substantially improve health outcomes for newborns. As the cost of genetic testing decreases, it is becoming an essential part of newborn screening. A genetic disorder can be caused by many mutation variants; therefore, an important decision is to determine which variants to search for (ie, the panel design), under a testing budget. The frequency of variants that cause a disorder and the incidence of the disorder vary by racial/ethnic group. Consequently, it is important to consider equity issues in panel design, so as to reduce disparities among different groups. We study the panel design problem using cystic fibrosis (CF) as a model disorder, considering the trade‐offs between equity and accuracy, under a limited budget. Most states use a genetic test in their CF screening protocol, but panel designs vary, and, due to cost, no state's panel includes all CF‐causing variants. We develop models that design equitable genetic testing panels, and compare them with panels that maximize sensitivity in the general population. Our case study, based on realistic CF data, highlights the value of equitable panels and provides important insight for newborn screening practices.     

Beyond the state: reconceptualising African security in the 21st century

Confronted with myriad security challenges, African states and the much-vaunted peace and security architecture of the African Union (AU) has proven not to be up to the challenge. Indeed, this is implicitly acknowledged by the AU itself if one considers the creation of such security structures as the African Mission in Somalia (AMISOM), which exists outside its peace and security architecture. This paper argues for a radical rethink of security structures on the African continent – one in which state structures of security coexist with newer forms of security actors, including private military companies (PMCs), community movements and the business sector. Whilst this shift in security actors is already happening on the ground, policymakers need to embrace this new reality.     

Combating Islamist radicalisation in South Africa

Is radical Islamism spreading in South Africa? The answer has to be an emphatic ‘yes’. When discussing issues of radicalisation in Africa, commentators often examine the case of Somalia's al-Shabaab or al-Qaeda's North African franchise, al-Qaeda in the Islamic Maghreb (AQIM). Very little attention is paid to radicalisation amongst South Africa's Muslim population. Yet, there is growing evidence that South Africa has come to play an important role in global jihadi networks, from the provision of safehouses and identity documents to the movement of funds and the existence of paramilitary camps for local and foreign jihadis. This paper aims to briefly examine radicalisation and its attendant sources in the country, as well as seeking ways to combat it utilising lessons learned from other countries. ‘Institutional socialisation’ by means of the sources of radicalisation, as well as the concept of what could be termed ‘the democratisation of jihad’ are discussed. The author also proposes ways to combat radicalisation in South Africa utilising lessons learned from other countries, concluding that issues of radicalisation and deradicalisation have to be dealt with on the part of both government and the South African Muslim community.     

A new importance sampling Monte Carlo method for a flow network reliability problem

The exact evaluation of the probability that the maximum st‐flow is greater than or equal to a fixed demand in a stochastic flow network is an NP‐hard problem. This limitation leads one to consider Monte Carlo alternatives. In this paper, we propose a new importance sampling Monte Carlo method. It is based on a recursive use of the state space decomposition methodology of Doulliez and Jamoulle during the simulation process. We show theoretically that the resulting estimator belongs to the variance‐reduction family and we give an upper bound on its variance. As shown by experimental tests, the new sampling principle offers, in many cases, substantial speedups with respect to a previous importance sampling based on the same decomposition procedure and its best performances are obtained when highly reliable networks are analyzed. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 204–228, 2002; DOI 10.1002/nav.10004     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.     

A location‐inventory model with lateral transshipments

We study an infinite horizon periodic stochastic inventory system consisting of retail outlets and customers located on a homogenous line segment. In each period, the total demand, generated by the customers on the line, is normally distributed. To better match supply and demand, we incorporate lateral transshipments. We propose a compact model in which the strategic decisions—the number and locations of retail outlets—are determined simultaneously with the operational decisions—the inventory replenishment and transshipment quantities. We find the optimal balance between the risk‐pooling considerations, which drive down the optimal number of retail outlets, and lateral transshipments, which drive up the optimal number of retail outlets. We also explore the sensitivity of the optimal number of retail outlets to various problem parameters. This article presents a novel way of integrating lateral transshipments in the context of an inventory‐location model. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Economic and environmental impacts of vertical and horizontal competition and integration

We explore the economic and environmental impacts of market structures (competition or integration at vertical and horizontal levels). We consider a bilateral duopoly consisting of two manufacturers and two retailers in which each manufacturer offers a wholesale price contract to the respective retailer. The manufacturers decide on wholesale prices and abatement efforts concerning pollution emissions related to manufacturing processes, whereas the retailers compete in quantities in the consumer market. To understand the comprehensive effects of market structures on economic competitiveness and environmental sustainability, we examine a measure of eco‐friendly social welfare, which is the ratio of social welfare and environmental pollution. Interestingly, we find that the market structures that have been believed to be more efficient are less efficient from a broader perspective: (1) double marginalization can generate higher eco‐friendly social welfare, and (2) horizontal competition between firms can result in lower eco‐friendly social welfare. Although vertical integration and horizontal competition yield greater social welfare by facilitating more production activities, these market structures often fail to induce sufficient abatement efforts to balance the polluting effect of the large volume, resulting in more significant environmental degradation. We also show that, despite the pollution‐curbing effect, higher emission penalties can result in less eco‐friendly social welfare. They can even curtail the abatement efforts of firms under particular circumstances. When products become more substitutable, the eco‐friendly social welfare can decrease depending upon the market structure.