The First Lumpy Skin Disease Outbreak in Thailand (2021): Epidemiological Features and Spatio-Temporal Analysis

The first outbreak of lumpy skin disease (LSD) in Thailand was reported in March 2021, but information on the epidemiological characteristics of the outbreak is very limited. The objectives of this study were to describe the epidemiological features of LSD outbreaks and to identify the outbreak spatio-temporal clusters. The LSD-affected farms located in Roi Et province were investigated by veterinary authorities under the outbreak response program. A designed questionnaire was used to obtain the data. Space-time permutation (STP) and Poisson space-time (Poisson ST) models were used to detect areas of high LSD incidence. The authorities identified 293 LSD outbreak farms located in four different districts during the period of March and the first week of April 2021. The overall morbidity and mortality of the affected cattle were 40.5 and 1.2%, respectively. The STP defined seven statistically significant clusters whereas only one cluster was identified by the Poisson ST model. Most of the clusters (n = 6) from the STP had a radius <7 km, and the number of LSD cases in those clusters varied in range of 3–51. On the other hand, the most likely cluster from the Poisson ST included LSD cases (n = 361) from 198 cattle farms with a radius of 17.07 km. This is the first report to provide an epidemiological overview and determine spatio-temporal clusters of the first LSD outbreak in cattle farms in Thailand. The findings from this study may serve as a baseline information for future epidemiological studies and support authorities to establish effective control programs for LSD in Thailand.

Containment of a multi-index B.1.1.7 outbreak on a university campus through a genomically-informed public health response

The first cluster of SARS-CoV-2 cases with lineage B.1.1.7 in the state of Michigan was identified through intensive university-led surveillance sampling and targeted sequencing. A collaborative investigation and response was conducted by the local and state health departments, and the campus and athletic medicine COVID-19 response teams, using S-gene target failure screening and rapid genomic sequencing to inform containment strategies. A total of 50 cases of B.1.1.7-lineage SARS-CoV-2 were identified in this outbreak, which was due to three coincident introductions of B.1.1.7-lineage SARS-CoV-2, all of which were genetically distinct from lineages which later circulated in the broader community. This investigation demonstrates the successful implementation of a genomically-informed outbreak response which can be extended to university campuses and other settings at high risk for rapid emergence of new variants.

SORMAS-Stats: A Novel Statistical Application for Real-time Estimation of Epidemiological Parameters of Communicable Diseases using Contact-tracing Data. (Preprint)

BACKGROUND The Surveillance Outbreak Response Management and Analysis System (SORMAS) contains a management module to support countries in epidemic response. It consists of documentation, linkage and follow-up of cases, contacts, and events. To allow SORMAS users to visualise, compute key surveillance indicators and estimate epidemiological parameters from such a network data in real time, we developed the SORMAS Statistics (SORMAS-Stats) application. OBJECTIVE The aim of this study is to describe the key visualisations, surveillance indicators and epidemiological parameters implemented in the SORMAS-Stats application, and illustrate the application of SORMAS-Stats to COVID-19 outbreak response. METHODS Based on literature review and user requests, we included the following visualisation and estimation of parameters in SORMAS-Stats: transmission network diagram, serial interval (SI), time-varying reproduction number (Rt), dispersion parameter (k) and additional surveillance indicators presented in graphs and tables. We estimated SI by fitting a lognormal, gamma, and Weibull distributions to the observed distribution of the number of days between symptoms onset dates of infector-infectee pairs. We estimated k by fitting a negative binomial distribution to the observed number of infectees per infector. We applied the Markov Chain Monte Carlo approach and estimated Rt using the incidence data and the observed SI data, computed from the transmission network data. RESULTS Using COVID-19 contact tracing data of confirmed cases reported between July 31, and October 29, 2021 in Bourgogne-Franche-Comté region of France, we constructed a network diagram containing 63570 nodes comprising 1.75% (1115/63570) events, 19.59% (12452/63570) case persons, and 78.66% (50003/63570) exposed persons, 1238 infector-infectee pairs, 3860 transmission chains with 24.69% (953/3860) having events as the index infector. The distribution with best fit to the observed SI data was lognormal distribution with mean 4.32 days (95% CI, 4.10–4.53 days). We estimated the dispersion parameter, k of 21.11 (95% CI, 7.57–34.66) and a reproductive number, R of 0.9 (95% CI, 0.58–0.60). The weekly estimated Rt values ranged from 0.80 to 1.61. CONCLUSIONS We provide an application for real-time estimation of epidemiological parameters, which are essential for informing outbreak response strategies. These estimates are commensurate with findings from previous studies. SORMAS-Stats application would greatly assist public health authorities in the regions using SORMAS or similar applications by providing extensive visualisations and computation of surveillance indicators.

Availability and Suitability of Digital Health Tools in Africa for Pandemic Control: Scoping Review and Cluster Analysis

Background Gaining oversight into the rapidly growing number of mobile health tools for surveillance or outbreak management in Africa has become a challenge. Objective The aim of this study is to map the functional portfolio of mobile health tools used for surveillance or outbreak management of communicable diseases in Africa. Methods We conducted a scoping review by combining data from a systematic review of the literature and a telephone survey of experts. We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines by searching for articles published between January 2010 and December 2020. In addition, we used the respondent-driven sampling method and conducted a telephone survey from October 2019 to February 2020 among representatives from national public health institutes from all African countries. We combined the findings and used a hierarchical clustering method to group the tools based on their functionalities (attributes). Results We identified 30 tools from 1914 publications and 45 responses from 52% (28/54) of African countries. Approximately 13% of the tools (4/30; Surveillance Outbreak Response Management and Analysis System, Go.Data, CommCare, and District Health Information Software 2) covered 93% (14/15) of the identified attributes. Of the 30 tools, 17 (59%) tools managed health event data, 20 (67%) managed case-based data, and 28 (97%) offered a dashboard. Clustering identified 2 exceptional attributes for outbreak management, namely contact follow-up (offered by 8/30, 27%, of the tools) and transmission network visualization (offered by Surveillance Outbreak Response Management and Analysis System and Go.Data). Conclusions There is a large range of tools in use; however, most of them do not offer a comprehensive set of attributes, resulting in the need for public health workers having to use multiple tools in parallel. Only 13% (4/30) of the tools cover most of the attributes, including those most relevant for response to the COVID-19 pandemic, such as laboratory interface, contact follow-up, and transmission network visualization.

A Conceptual Framework for Analysing Partnership and Synergy in a Global Health Alliance: Case of the UK Public Health Rapid Support Team (UK-PHRST)

ABSTRACT Partnerships have become increasingly important in addressing complex global health challenges, a reality exemplified by the COVID-19 pandemic and previous infectious disease epidemics. Partnerships offer opportunities to create synergistic outcomes by capitalising on complimentary skills, knowledge and resources. Despite the importance of understanding partnership functioning, research on collaboration is sparse and fragmented, with few conceptual frameworks applied to evaluate real-life partnerships in global health. In this study, we aimed to adapt and apply the Bergan Model of Collaborative Functioning (BMCF) to analyse partnership functioning in the UK Public Health Rapid Support Team (UK-PHRST), a government-academic partnership, dedicated to outbreak response and research in low- and middle-income countries. We conducted a literature review identifying important elements to adapt the framework, followed by a qualitative case study to characterise how each element, and the dynamics between them, influenced functioning in the UK-PHRST, exploring emerging themes to further refine the framework. Elements of the BMCF that our study reinforced as important included the partnership’s mission, partner resources (skills, expertise, networks), leadership, the external environment, management systems, and communication. Additional elements identified in the literature and critical to partnership functioning of the UK-PHRST included governance and financial structures adopted, trust and power balance, organisational culture, strategy, and evaluation and knowledge management. Because of the way the UK-PHRST was structured, fostering team cohesion was an important indicator of synergy, alongside collaborative advantage. Dividing the funding and governance equally between organisations was considered crucial for maintaining institutional balance, however, diverse organisational cultures, weak communication practices and perceived power imbalances compromised team cohesion. Our analysis allowed us to make recommendations to improve partnership functioning at a critical time in the evolution of the UK-PHRST. The analysis approach and framework presented here can be used to evaluate and strengthen the management of global health partnerships to realise synergy.

Assessing Mechanisms Underlying the Sharing of Official and Unofficial Information during a Pandemic

The COVID-19 disease outbreak has seen mixed information flows comprising top-down communication from health authorities to the public and citizen-to-citizen communication. This study aimed to identify mechanisms underlying the sharing of official versus unofficial information during the outbreak. Survey findings based on a nationally representative U.S. sample (N = 856) showed that individuals’ predispositions affected their information consumption and affective experiences, leading to distinct types of information-sharing behaviors. While anger toward the U.S. government’s outbreak response was directly associated with unofficial information sharing, anxiety was directly associated with official information sharing. These findings enhance our understanding of the propagation of different kinds of pandemic information and provide implications for public education on information verification based on source authoritativeness.

A systematic review on mobile health applications for foodborne disease outbreak management

Background Foodborne disease outbreaks are common and notifiable in South Africa; however, they are rarely reported and poorly investigated. Surveillance data from the notification system is suboptimal and limited, and does not provide adequate information to guide public health action and inform policy. We performed a systematic review of published literature to identify mobile application-based outbreak response systems for managing foodborne disease outbreaks and to determine the elements that the system requires to generate foodborne disease data needed for public action. Methods Studies were identified through literature searches using online databases on PubMed/Medline, CINAHL, Academic Search Complete, Greenfile, Library, Information Science & Technology. Search was limited to studies published in English during the period January 1990 to November 2020. Search strategy included various terms in varying combinations with Boolean phrases “OR” and “AND”. Data were collected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. A standardised data collection tool was used to extract and summarise information from identified studies. We assessed qualities of mobile applications by looking at the operating system, system type, basic features and functionalities they offer for foodborne disease outbreak management. Results Five hundred and twenty-eight (528) publications were identified, of which 48 were duplicates. Of the remaining 480 studies, 2.9% (14/480) were assessed for eligibility. Only one of the 14 studies met the inclusion criteria and reported on one mobile health application named MyMAFI (My Mobile Apps for Field Investigation). There was lack of detailed information on the application characteristics. However, based on minimal information available, MyMAFI demonstrated the ability to generate line lists, reports and offered functionalities for outbreak verification and epidemiological investigation. Availability of other key components such as environmental and laboratory investigations were unknown. Conclusions There is limited use of mobile applications on management of foodborne disease outbreaks. Efforts should be made to set up systems and develop applications that can improve data collection and quality of foodborne disease outbreak investigations.

Civilian-military malaria outbreak response in Thailand: an example of multi-stakeholder engagement for malaria elimination

Background In April 2017, the Thai Ministry of Public Health (MoPH) was alerted to a potential malaria outbreak among civilians and military personnel in Sisaket Province, a highly forested area bordering Cambodia. The objective of this study was to present findings from the joint civilian-military outbreak response. Methods A mixed-methods approach was used to assess risk factors among cases reported during the 2017 Sisaket malaria outbreak. Routine malaria surveillance data from January 2013 to March 2018 obtained from public and military medical reporting systems and key informant interviews (KIIs) (n = 72) were used to develop hypotheses about potential factors contributing to the outbreak. Joint civilian-military response activities included entomological surveys, mass screen and treat (MSAT) and vector control campaigns, and scale-up of the “1–3–7” reactive case detection approach among civilians alongside a pilot “1–3–7” study conducted by the Royal Thai Army (RTA). Results Between May–July 2017, the monthly number of MoPH-reported cases surpassed the epidemic threshold. Outbreak cases detected through the MoPH mainly consisted of Thai males (87%), working as rubber tappers (62%) or military/border police (15%), and Plasmodium vivax infections (73%). Compared to cases from the previous year (May–July 2016), outbreak cases were more likely to be rubber tappers (OR = 14.89 [95% CI: 5.79–38.29]; p < 0.001) and infected with P. vivax (OR=2.32 [1.27–4.22]; p = 0.006). Themes from KIIs were congruent with findings from routine surveillance data. Though limited risk factor information was available from military cases, findings from RTA’s “1–3–7” study indicated transmission was likely occurring outside military bases. Data from entomological surveys and MSAT campaigns support this hypothesis, as vectors were mostly exophagic and parasite prevalence from MSAT campaigns was very low (range: 0-0.7% by PCR/microscopy). Conclusions In 2017, an outbreak of mainly P. vivax occurred in Sisaket Province, affecting mainly military and rubber tappers. Vector control use was limited to the home/military barracks, indicating that additional interventions were needed during high-risk forest travel periods. Importantly, this outbreak catalyzed joint civilian-military collaborations and integration of the RTA into the national malaria elimination strategy (NMES). The Sisaket outbreak response serves as an example of how civilian and military public health systems can collaborate to advance national malaria elimination goals in Southeast Asia and beyond.