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1.  Analyzing Personalized Policies for Online Biometric Verification 
PLoS ONE  2014;9(5):e94087.
Motivated by India’s nationwide biometric program for social inclusion, we analyze verification (i.e., one-to-one matching) in the case where we possess similarity scores for 10 fingerprints and two irises between a resident’s biometric images at enrollment and his biometric images during his first verification. At subsequent verifications, we allow individualized strategies based on these 12 scores: we acquire a subset of the 12 images, get new scores for this subset that quantify the similarity to the corresponding enrollment images, and use the likelihood ratio (i.e., the likelihood of observing these scores if the resident is genuine divided by the corresponding likelihood if the resident is an imposter) to decide whether a resident is genuine or an imposter. We also consider two-stage policies, where additional images are acquired in a second stage if the first-stage results are inconclusive. Using performance data from India’s program, we develop a new probabilistic model for the joint distribution of the 12 similarity scores and find near-optimal individualized strategies that minimize the false reject rate (FRR) subject to constraints on the false accept rate (FAR) and mean verification delay for each resident. Our individualized policies achieve the same FRR as a policy that acquires (and optimally fuses) 12 biometrics for each resident, which represents a five (four, respectively) log reduction in FRR relative to fingerprint (iris, respectively) policies previously proposed for India’s biometric program. The mean delay is sec for our proposed policy, compared to 30 sec for a policy that acquires one fingerprint and 107 sec for a policy that acquires all 12 biometrics. This policy acquires iris scans from 32–41% of residents (depending on the FAR) and acquires an average of 1.3 fingerprints per resident.
doi:10.1371/journal.pone.0094087
PMCID: PMC4006790  PMID: 24787752
2.  Assessing Screening Policies for Childhood Obesity 
Obesity (Silver Spring, Md.)  2012;20(7):1437-1443.
To address growing concerns over childhood obesity, the United States Preventive Services Task Force (USPSTF) recently recommended that children undergo obesity screening beginning at age 6 [1]. An Expert Committee recommends starting at age 2 [2]. Analysis is needed to assess these recommendations and investigate whether there are better alternatives. We model the age- and sex-specific population-wide distribution of body mass index (BMI) through age 18 using National Longitudinal Survey of Youth data [3]. The impact of treatment on BMI is estimated using the targeted systematic review performed to aid the USPSTF [4]. The prevalence of hypertension and diabetes at age 40 are estimated from the Panel Study of Income Dynamics [5]. We fix the screening interval at 2 years, and derive the age- and sex-dependent BMI thresholds that minimize adult disease prevalence, subject to referring a specified percentage of children for treatment yearly. We compare this optimal biennial policy to biennial versions of the USPSTF and Expert Committee recommendations. Compared to the USPSTF recommendation, the optimal policy reduces adult disease prevalence by 3% in relative terms (the absolute reductions are < 1%) at the same treatment referral rate, or achieves the same disease prevalence at a 28% reduction in treatment referral rate. If compared to the Expert Committee recommendation, the reductions change to 6% and 40%, respectively. The optimal policy treats mostly 16 year olds and few children under age 14. Our results suggest that adult disease is minimized by focusing childhood obesity screening and treatment on older adolescents.
doi:10.1038/oby.2011.373
PMCID: PMC3997741  PMID: 22240724
3.  Analyzing Screening Policies for Childhood Obesity 
Management science  2012;59(4):782-795.
Due to the health and economic costs of childhood obesity, coupled with studies suggesting the benefits of comprehensive (dietary, physical activity and behavioral counseling) intervention, the United States Preventive Services Task Force recently recommended childhood screening and intervention for obesity beginning at age six. Using a longitudinal data set consisting of the body mass index of 3164 children up to age 18 and another longitudinal data set containing the body mass index at ages 18 and 40 and the presence or absence of disease (hypertension and diabetes) at age 40 for 747 people, we formulate and numerically solve – separately for boys and girls – a dynamic programming problem for the optimal biennial (i.e., at ages 2, 4, …, 16) obesity screening thresholds. Unlike most screening problem formulations, we take a societal viewpoint, where the state of the system at each age is the population-wide probability density function of the body mass index. Compared to the biennial version of the task force’s recommendation, the screening thresholds derived from the dynamic program achieve a relative reduction in disease prevalence of 3% at the same screening (and treatment) cost, or – due to the flatness of the disease vs. screening tradeoff curve – achieves the same disease prevalence at a 28% relative reduction in cost. Compared to the task force’s policy, which uses the 95th percentile of body mass index (from cross-sectional growth charts tabulated by the Centers for Disease Control and Prevention) as the screening threshold for each age, the dynamic programming policy treats mostly 16 year olds (including many who are not obese) and very few males under 14 years old. While our results suggest that adult hypertension and diabetes are minimized by focusing childhood obesity screening and treatment on older adolescents, the shortcomings in the available data and the narrowness of the medical outcomes considered prevent us from making a recommendation about childhood obesity screening policies.
doi:10.1287/mnsc.1120.1587
PMCID: PMC3744381  PMID: 23956465
4.  Quantifying and Exploiting the Age Dependence in the Effect of Supplementary Food for Child Undernutrition 
PLoS ONE  2014;9(6):e99632.
Motivated by the lack of randomized controlled trials with an intervention-free control arm in the area of child undernutrition, we fit a trivariate model of weight-for-age z score (WAZ), height-for-age z score (HAZ) and diarrhea status to data from an observational study of supplementary feeding (100 kCal/day for children with WAZ ) in 17 Guatemalan communities. Incorporating time lags, intention to treat (i.e., to give supplementary food), seasonality and age interactions, we estimate how the effect of supplementary food on WAZ, HAZ and diarrhea status varies with a child’s age. We find that the effect of supplementary food on all 3 metrics decreases linearly with age from 6 to 20 mo and has little effect after 20 mo. We derive 2 food allocation policies that myopically (i.e., looking ahead 2 mo) minimize either the underweight or stunting severity – i.e., the sum of squared WAZ or HAZ scores for all children with WAZ or HAZ . A simulation study based on the statistical model predicts that the 2 derived policies reduce the underweight severity (averaged over all ages) by 13.6–14.1% and reduce the stunting severity at age 60 mo by 7.1–8.0% relative to the policy currently in use, where all policies have a budget that feeds % of children. While these findings need to be confirmed on additional data sets, it appears that in a low-dose (100 kCal/day) supplementary feeding setting in Guatemala, allocating food primarily to 6–12 mo infants can reduce the severity of underweight and stunting.
doi:10.1371/journal.pone.0099632
PMCID: PMC4072673  PMID: 24967745
5.  HEPA/Vaccine Plan for Indoor Anthrax Remediation 
Emerging Infectious Diseases  2005;11(1):69-76.
A mathematical model suggests that a HEPA/vaccine approach is viable for most buildings after a large-scale anthrax attack.
We developed a mathematical model to compare 2 indoor remediation strategies in the aftermath of an outdoor release of 1.5 kg of anthrax spores in lower Manhattan. The 2 strategies are the fumigation approach used after the 2001 postal anthrax attack and a HEPA/vaccine plan, which relies on HEPA vacuuming, HEPA air cleaners, and vaccination of reoccupants. The HEPA/vaccine approach leads to few anthrax cases among reoccupants if applied to all but the most heavily contaminated buildings, and recovery is much faster than under the decades-long fumigation plan. Only modest environmental sampling is needed. A surge capacity of 10,000 to 20,000 Hazmat workers is required to perform remediation within 6 to 12 months and to avoid permanent mass relocation. Because of the possibility of a campaign of terrorist attacks, serious consideration should be given to allowing or encouraging voluntary self-service cleaning of lightly contaminated rooms by age-appropriate, vaccinated, partially protected (through masks or hoods) reoccupants or owners.
doi:10.3201/eid1101.040635
PMCID: PMC3294362  PMID: 15705325
research; HEPA filter; anthrax; mathematical model; bioterrorism; remediation; vaccine
6.  Detecting Bioterror Attacks by Screening Blood Donors: A Best-Case Analysis 
Emerging Infectious Diseases  2003;9(8):909-914.
To assess whether screening blood donors could provide early warning of a bioterror attack, we combined stochastic models of blood donation and the workings of blood tests with an epidemic model to derive the probability distribution of the time to detect an attack under assumptions favorable to blood donor screening. Comparing the attack detection delay to the incubation times of the most feared bioterror agents shows that even under such optimistic conditions, victims of a bioterror attack would likely exhibit symptoms before the attack was detected through blood donor screening. For example, an attack infecting 100 persons with a noncontagious agent such as Bacillus anthracis would only have a 26% chance of being detected within 25 days; yet, at an assumed additional charge of $10 per test, donor screening would cost $139 million per year. Furthermore, even if screening tests were 99.99% specific, 1,390 false-positive results would occur each year. Therefore, screening blood donors for bioterror agents should not be used to detect a bioterror attack.
doi:10.3201/eid0908.030079
PMCID: PMC3020608  PMID: 12967486
bioterrorism; blood donors; disease outbreaks; probability; stochastic processes; Perspective

Results 1-6 (6)