The Global Task Force on Cholera Control (GTFCC) created a strategy for early outbreak detection, hotspot identification, and resource mobilization coordination in response to the Yemeni cholera epidemic. This strategy requires a systematic approach for defining and classifying outbreak signatures, or the profile of an epidemic curve and its features. We used publicly available data to quantify outbreak features of the ongoing cholera epidemic in Yemen and clustered governorates using an adaptive time series methodology. We characterized outbreak signatures and identified clusters using a weekly time series of cholera rates in 20 Yemeni governorates and nationally from 4 September 2016 through 29 December 2019 as reported by the World Health Organization (WHO). We quantified critical points and periods using Kolmogorov-Zurbenko adaptive filter methodology. We assigned governorates into six clusters sharing similar outbreak signatures, according to similarities in critical points, critical periods, and the magnitude of peak rates. We identified four national outbreak waves beginning on 12 September 2016, 6 March 2017, 28 May 2018, and 28 January 2019. Among six identified clusters, we classified a core regional hotspot in Sana'a, Sana'a City, and Al-Hudaydah-the expected origin of the national outbreak. The five additional clusters differed in Wave 2 and Wave 3 peak frequency, timing, magnitude, and geographic location. As of 29 December 2019, no governorates had returned to pre-Wave 1 levels. The detected similarity in outbreak signatures suggests potentially shared environmental and human-made drivers of infection; the heterogeneity in outbreak signatures implies the potential traveling waves outwards from the core regional hotspot that could be governed by factors that deserve further investigation.

Widespread destruction from the Yemeni Civil War (2014-present) triggered the world's largest cholera outbreak. We compiled a comprehensive health dataset and created dynamic maps to demonstrate spatiotemporal changes in cholera infections and war conflicts. We aligned and merged daily, weekly, and monthly epidemiological bulletins of confirmed cholera infections and daily conflict events and fatality records to create a dataset of weekly time series for Yemen at the governorate level (subnational regions administered by governors) from 4 January 2016 through 29 December 2019. We demonstrated the use of dynamic mapping for tracing the onset and spread of infection and manmade factors that amplify the outbreak. We report curated data and visualization techniques to further uncover associations between infectious disease outbreaks and risk factors and to better coordinate humanitarian aid and relief efforts during complex emergencies.

Critical temporal changes such as weekly fluctuations in surveillance systems often reflect changes in laboratory testing capacity, access to testing or healthcare facilities, or testing preferences. Many studies have noted but few have described day-of-the-week (DoW) effects in SARS-CoV-2 surveillance over the major waves of the novel coronavirus 2019 pandemic (COVID-19). We examined DoW effects by non-pharmaceutical intervention phases adjusting for wave-specific signatures using the John Hopkins University's (JHU's) Center for Systems Science and Engineering (CSSE) COVID-19 data repository from 2 March 2020 through 7 November 2021 in Middlesex County, Massachusetts, USA. We cross-referenced JHU's data with Massachusetts Department of Public Health (MDPH) COVID-19 records to reconcile inconsistent reporting. We created a calendar of statewide non-pharmaceutical intervention phases and defined the critical periods and timepoints of outbreak signatures for reported tests, cases, and deaths using Kolmogorov-Zurbenko adaptive filters. We determined that daily death counts had no DoW effects; tests were twice as likely to be reported on weekdays than weekends with decreasing effect sizes across intervention phases. Cases were also twice as likely to be reported on Tuesdays-Fridays (RR = 1.90-2.69 [95%CI: 1.38-4.08]) in the most stringent phases and half as likely to be reported on Mondays and Tuesdays (RR = 0.51-0.93 [0.44, 0.97]) in less stringent phases compared to Sundays; indicating temporal changes in laboratory testing practices and use of healthcare facilities. Understanding the DoW effects in daily surveillance records is valuable to better anticipate fluctuations in SARS-CoV-2 testing and manage appropriate workflow. We encourage health authorities to establish standardized reporting protocols.

Military field hospitals typically provide essential medical care in combat zones. In recent years, the United States (US) Army has deployed these facilities to assist domestic humanitarian emergency and natural disaster response efforts. As part of the nation's whole-of-government approach to the coronavirus disease (COVID-19) pandemic, directed by the Federal Emergency Management Agency and the Department of Health and Human Services, during New York City's (NYC) initial surge of COVID-19, from 26 March to 1 May 2020, the US Army erected the Javits New York Medical Station (JNYMS) field hospital to support the city's overwhelmed healthcare system. The JNYMS tasked a nutrition operations team (NuOp) to provide patient meals and clinical nutrition evaluations to convalescent COVID-19 patients. However, few guidelines were available for conducting emergency nutrition and dietary response efforts prior to the field hospital's opening. In this case study, we summarize the experiences of the NuOp at the JNYMS field hospital, to disseminate the best practices for future field hospital deployments. We then explain the challenges in service performance, due to information, personnel, supply, and equipment shortages. We conclude by describing the nutrition service protocols that have been implemented to overcome these challenges, including creating a standardized recordkeeping system for patient nutrition information, developing a meal tracking system to forecast meal requirements with food service contractors, and establishing a training and staffing model for military-to-civilian command transition. We highlight the need for a standardized humanitarian emergency nutrition service response framework and propose a Nutrition Response Toolkit for Humanitarian Crises, which offers low-cost, easily adaptable operational protocols for implementation in future field hospital deployments.