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Background: The burden of diarrheal diseases remains high among children in low-income countries. Enteropathogens are challenging to control because they are transmitted via multiple pathways. Chickens are an important animal protein source, but live chickens and their products are often highly contaminated with enteropathogens. Objectives: We conducted this study to a) understand the contribution of multiple transmission pathways to the force of infection of Campylobacter spp. and nontyphoidal Salmonella spp., b) quantify the potential impact of reducing each pathway on human infection, and c) quantify hypothesized pathway reduction from the context of Maputo, Mozambique. Methods: We developed transmission models for Campylobacter and Salmonella that captured person-to-person, water-to-person, food-to-person, soil-to-person, animal-to-person, and all-other-sources-to-person in an urban, low-income setting in Mozambique. We calibrated these models using prevalence data from Maputo, Mozambique and estimates of attributable fraction of transmission pathways for the region. We simulated the prevalence of human infection after reducing transmission through each pathway. Results: Simulation results indicated that if foodborne transmission were reduced by 90%, the prevalence of Campylobacter and Salmonella infection would decline by [52.2%; 95% credible interval (CrI): 39.7, 63.8] and (46.9%; 95% CrI: 39, 55.4), respectively. Interruption of any other pathway did not have a substantial impact. Combined with survey and microbiology data, if contamination of broiler chicken meat at informal markets in Maputo could be reduced by 90%, the total infection of Campylobacter and Salmonella could be reduced by 21% (16-26%) and 12% (10-13%), respectively. Discussion: Our transmission models showed that the foodborne transmission has to be reduced to control enteropathogen infections in our study site, and likely in other similar contexts, but mitigation of this transmission pathway has not received sufficient attention. Our model can serve as a tool to identify effective mitigation opportunities to control zoonotic enteropathogens. 

Abstract The astrometric precision and accuracy of an imaging camera is often limited by geometric optical distortions. These must be calibrated and removed to measure precise proper motions, orbits, and gravitationally lensed positions of interesting astronomical objects. Here, we derive a distortion solution for the OSIRIS Imager fed by the Keck I adaptive optics system at the W. M. Keck Observatory. The distortion solution was derived from images of the dense globular clusters M15 and M92 taken with OSIRIS in 2020 and 2021. The set of 403 starlists, each containing ∼1000 stars, were compared to reference Hubble catalogs to measure the distortion-induced positional differences. OSIRIS was opened and optically realigned in 2020 November and the distortion solutions before and after the opening show slight differences at the ∼20 mas level. We find that the OSIRIS distortion closely matches the designed optical model: large, reaching 20 pixels at the corners, but mostly low order, with the majority of the distortion in the 2nd-order mode. After applying the new distortion correction, we find a median residual of [x, y] = [0.052, 0.056] pixels ([0.51, 0.56] mas) for the 2020 solution, and [x, y] = [0.081, 0.071] pixels ([0.80, 0.71] mas) for the 2021 solution. Comparison between NIRC2 images and OSIRIS images of the Galactic center show that the mean astrometric difference between the two instruments reduces from 10.7 standard deviations to 1.7 standard deviations when the OSIRIS distortion solution is applied. The distortion model is included in the Keck AO Imaging data-reduction pipeline and is available for use on OSIRIS data. 

Randomized controlled trials (RCTs) evaluate hypotheses in specific contexts and are often considered the gold standard of evidence for infectious disease interventions, but their results cannot immediately generalize to other contexts (e.g., different populations, interventions, or disease burdens). Mechanistic models are one approach to generalizing findings between contexts, but infectious disease transmission models (IDTMs) are not immediately suited for analyzing RCTs, since they often rely on time-series surveillance data. We developed an IDTM framework to explain relative risk outcomes of an infectious disease RCT and applied it to a water, sanitation, and hygiene (WASH) RCT. This model can generalize the RCT results to other contexts and conditions. We developed this compartmental IDTM framework to account for key WASH RCT factors: i) transmission across multiple environmental pathways, ii) multiple interventions applied individually and in combination, iii) adherence to interventions or preexisting conditions, and iv) the impact of individuals not enrolled in the study. We employed a hybrid sampling and estimation framework to obtain posterior estimates of mechanistic parameter sets consistent with empirical outcomes. We illustrated our model using WASH Benefits Bangladesh RCT data (n = 17,187). Our model reproduced reported diarrheal prevalence in this RCT. The baseline estimate of the basic reproduction number R 0 for the control arm (1.10, 95% CrI: 1.07, 1.16) corresponded to an endemic prevalence of 9.5% (95% CrI: 7.4, 13.7%) in the absence of interventions or preexisting WASH conditions. No single pathway was likely able to sustain transmission: pathway-specific R 0 s for water, fomites, and all other pathways were 0.42 (95% CrI: 0.03, 0.97), 0.20 (95% CrI: 0.02, 0.59), and 0.48 (95% CrI: 0.02, 0.94), respectively. An IDTM approach to evaluating RCTs can complement RCT analysis by providing a rigorous framework for generating data-driven hypotheses that explain trial findings, particularly unexpected null results, opening up existing data to deeper epidemiological understanding. 

We calculate an optical distortion solution for the OSIRIS Imager on the Keck I telescope, by matching observations of globular clusters to a Hubble reference catalogue. This solution can be applied to correct astrometric distortions in OSIRIS frames, improving the astrometric accuracy of observations. We model the distortion with a 5th order Legendre polynomial. The distortion we find matches the expected OSIRIS distortion, and has a fit error of 0.6 mas, but has large residuals of 7 mas. We are currently iterating on an improved reference frame to improve the residual. Additionally, we have installed the Precision Calibration Unit (PCU) on the Keck I optical bench, which will generates an artificial grid of stars for use in future distortion calculations. 

Recently developed scales aim to advance understanding of household water insecurity and inform interventions to address this critical global problem. The relative severity of items included in household water insecurity scales has been established as an inverse of the proportion of the population that reports experiencing the item. Here, we assess subjective perceptions of scale item severity among people who experience household water insecurity. In 2017, we surveyed 259 women in Amhara, Ethiopia, assessing both experiences of water insecurity and perceptions of item severity using a pictorial scale. The mean subjective severity of most items was at the high end of our pictorial scale. Subjective severity of items was not associated with whether or not a participant experienced the item in the last thirty days, with a participant’s summary household water insecurity score, or with rural versus peri-urban residence, but was consistently associated with community of residence. Item severity as defined by the proportion of the population experiencing the item aligned with average perceptions of item severity, with one exception: drinking water that might not be safe. We discuss these findings’ implications for water insecurity measurement, evaluation of interventions, and studies of the relationship between water insecurity and psychological distress. 

We present the status and plans for the Keck All sky Precision Adaptive optics (KAPA) program. KAPA includes (1) an upgrade to the Keck I laser guide star adaptive optics (AO) facility to improve image quality and sky coverage, (2) the inclusion of AO telemetry-based point spread function estimates with all science exposures, (3) four key science programs, and (4) an educational component focused on broadening the participation of women and underrepresented groups in instrumentation. For this conference we focus on the KAPA upgrades since the 2020 SPIE proceedings1 including implementation of a laser asterism generator, wavefront sensor, real-time controller, asterism and turbulence simulators, the laser tomography system itself along with new operations software and science tools, and modifications to an existing near-infrared tip-tilt sensor to support multiple natural guide star and focus measurements. We will also report on the results of daytime and on-sky calibrations and testing. 

Abstract Water security requires not only sufficient availability of and access to safe and acceptable quality for domestic uses, but also fair distribution within and across populations. However, a key research gap remains in understanding water security inequality and its dynamics, which in turn creates an impediment to tracking progress towards sustainable development. Therefore, we analyse the inequality of water security using data from 7603 households across 28 sites in 22 low- and middle-income countries, measured using the Household Water Insecurity Experiences Scale. Here we show an inverted-U shaped relationship between site water security and inequality of household water security. This Kuznets-like curve suggests a process that as water security grows, the inequality of water security first increases then decreases. This research extends the Kuznets curve applications and introduces the Development Kuznets Curve concept. Its practical implications support building water security and achieving more fair, inclusive, and sustainable development.