Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Cholera outbreak in districts around Lake Chilwa, Malawi: Lessons learned

BackgroundCholera is endemic in Malawi with seasonal outbreaks during the wet season. People living around Lake Chilwa rely on the lake for their water supply. From May 2009 to May 2010, a cholera outbreak occurred in fishing communities around Lake Chilwa. This paper describes the outbreak response and lessons learned for prevention and management of future outbreaks.MethodsStarting in January 2010, Médecins Sans Frontières (MSF) helped District Health Management Teams (DHMTs) to distribute educational materials, water disinfectant and hygiene supplies, and oral rehydration solution (ORS) in fishing communities. MSF also supported case management by mentoring health workers and providing equipment and supplies.ResultsA total of 1,171 cholera cases and 21 deaths were reported in the districts around the lake, with cases also being reported on the Mozambican side of the lake. The attack rate was highest among people living on or around the lake, particularly among fishermen. Samples of lake water had high turbidity conducive to the propagation of Vibrio cholerae.ConclusionA number of practical measures could be taken to prevent future outbreaks and to manage outbreaks more effectively. These measures should address surveillance, environmental management, outbreak preparedness, and case management

Modelling eggshell maculation

The eggshells of many avian species are characterised by distinctive patterns of maculation, consisting of speckles, spots, blotches or streaks, the spatial-statistical properties of which vary considerably between (and often within) species. Understanding the mechanisms underlying the production of eggshell maculation would enable us to explore the costs and constraints on the evolution of maculation patterns, but as yet this area is surprisingly understudied. Here I present a simple model of eggshell maculation, which is based on the known biology of pigment deposition, and which can produce a range of realistic maculation patterns. In particular, it provides an explanation for previous observations of maculation heterogeneity and diversity, and allows testable predictions to be made regarding maculation patterns, including a possible signalling role

Combinatorial quorum sensing allows bacteria to resolve their social and physical environment

Quorum sensing (QS) is a cell–cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay betweeallyn its two primary signal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic “AND-gate” responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results support a new functional hypothesis for the use of multiple signals and, more generally, show that bacteria are capable of combinatorial communication

CD4 testing at clinics to assess eligibility for Antiretroviral therapy

BackgroundIn 2011, the Ministry of Health raised the CD4 threshold for antiretroviral therapy (ART) eligibility from <250 cells/μl and <350 cells/μl, but at the same time only 8.8% of facilities in Malawi with HIV services provided CD4 testing. We conducted a record review at 10 rural clinics in Thyolo District to assess the impact of introducing CD4 testing on identifying patients eligible for ART.Methods:We abstracted CD4 counts of all ART-naïve, HIV-infected patients with WHO clinical stages 1 and 2 and an initial CD4 test between May 2008 and June 2009. At four clinics, we also abstracted CD4 counts of patients not initially eligible for ART who were retested before April 2010.ResultsOf 1,113 patients tested, the initial CD4 was “≤250 cells/μl” and “≤350 cells/μl” in 534 (48.0%). Of 203 patients with follow-up results, the most recent CD4 was ≤250 cells/μl in 34 (24.5%), and ≤350 cells/μl in 64 (46.0%).ConclusionsCD4 testing in rural clinics is feasible and identifies many patients eligible for ART who would not be identified without CD4 testing. CD4 testing needs to be scaled-up to identify patients eligible for ART. ART services need to be scaled-up concurrently to meet the resulting increased demand

A spatial analysis of giardiasis and cryptosporidiosis in relation to public water supply distribution in North West England

Giardia and Cryptosporidium are both waterborne parasites and leading causes of gastroenteritis. Although specimens from diarrhoeic patients are routinely examined for Cryptosporidium, they are often not examined for Giardia so many cases go undiagnosed. Since 2002, all faecal specimens in Central Lancashire have been tested for infection with Giardia and Cryptosporidium. The aim of this paper is to gain insight into the factors contributing to giardiasis and cryptosporidiosis, including evidence of transmission via drinking water. Our analysis found a higher risk of both conditions for young children and a second peak in risk of giardiasis in adults. There was a significantly higher risk of giardiasis for males and a higher risk of cryptosporidiosis for females. The geographical location was significant, with an increased risk in the north. Residence in an area with increased supply from one water treatment works was a significant predictor for cryptosporidiosis. © 2018 Elsevier Lt

Asthma exacerbation and proximity of residence to major roads: a population-based matched case-control study among the pediatric Medicaid population in Detroit, Michigan

<p>Abstract</p> <p>Background</p> <p>The relationship between asthma and traffic-related pollutants has received considerable attention. The use of individual-level exposure measures, such as residence location or proximity to emission sources, may avoid ecological biases.</p> <p>Method</p> <p>This study focused on the pediatric Medicaid population in Detroit, MI, a high-risk population for asthma-related events. A population-based matched case-control analysis was used to investigate associations between acute asthma outcomes and proximity of residence to major roads, including freeways. Asthma cases were identified as all children who made at least one asthma claim, including inpatient and emergency department visits, during the three-year study period, 2004-06. Individually matched controls were randomly selected from the rest of the Medicaid population on the basis of non-respiratory related illness. We used conditional logistic regression with distance as both categorical and continuous variables, and examined non-linear relationships with distance using polynomial splines. The conditional logistic regression models were then extended by considering multiple asthma states (based on the frequency of acute asthma outcomes) using polychotomous conditional logistic regression.</p> <p>Results</p> <p>Asthma events were associated with proximity to primary roads with an odds ratio of 0.97 (95% CI: 0.94, 0.99) for a 1 km increase in distance using conditional logistic regression, implying that asthma events are less likely as the distance between the residence and a primary road increases. Similar relationships and effect sizes were found using polychotomous conditional logistic regression. Another plausible exposure metric, a reduced form response surface model that represents atmospheric dispersion of pollutants from roads, was not associated under that exposure model.</p> <p>Conclusions</p> <p>There is moderately strong evidence of elevated risk of asthma close to major roads based on the results obtained in this population-based matched case-control study.</p

Careful prior specification avoids incautious inference for log-Gaussian Cox point processes

The BCI forest dynamics research project was founded by S.P. Hubbell and R.B. Foster and is now managed by R. Condit, S. Lao, and R. Perez under the Center for Tropical Forest Science and the Smithsonian Tropical Research in Panama. Numerous organizations have provided funding, principally the U.S. National Science Foundation, and hundreds of field workers have contributed. The data used can be requested and generally granted at http://ctfs.si.edudatarequest. Kriged estimates for concentration of the soil nutrients were downloaded from http://ctfs.si.edu/webatlas/datasets/bci/soilmaps/BCIsoil.html. We acknowledge the principal investigators that were responsible for collecting and analysing the soil maps (Jim Dallin, Robert John, Kyle Harms, Robert Stallard and Joe Yavitt), the funding sources (NSF DEB021104,021115, 0212284,0212818 and OISE 0314581, STRI Soils Initiative and CTFS) and field assistants (Paolo Segre and Juan Di Trani).Peer reviewedPostprin