A global analysis of One Health Networks and the proliferation of One Health collaborations.

There has been a renewed focus on threats to the human-animal-environment interface as a result of the COVID-19 pandemic, and investments in One Health collaborations are expected to increase. Efforts to monitor the development of One Health Networks (OHNs) are essential to avoid duplication or misalignment of investments. This Series paper shows the global distribution of existing OHNs and assesses their collective characteristics to identify potential deficits in the ways OHNs have formed and to help increase the effectiveness of investments. We searched PubMed, Google, Google Scholar, and relevant conference websites for potential OHNs and identified 184 worldwide for further analysis. We developed four case studies to show important findings from our research and exemplify best practices in One Health operationalisation. Our findings show that, although more OHNs were formed in the past 10 years than in the preceding decade, investment in OHNs has not been equitably distributed; more OHNs are formed and headquartered in Europe than in any other region, and emerging infections and novel pathogens were the priority focus area for most OHNs, with fewer OHNs focusing on other important hazards and pressing threats to health security. We found substantial deficits in the OHNs collaboration model regarding the diversity of stakeholder and sector representation, which we argue impedes effective and equitable OHN formation and contributes to other imbalances in OHN distribution and priorities. These findings are supported by previous evidence that shows the skewed investment in One Health thus far. The increased attention to One Health after the COVID-19 pandemic is an opportunity to focus efforts and resources to areas that need them most. Analyses, such as this Series paper, should be used to establish databases and repositories of OHNs worldwide. Increased attention should then be given to understanding existing resource allocation and distribution patterns, establish more egalitarian networks that encompass the breadth of One Health issues, and serve communities most affected by emerging, re-emerging, or endemic threats at the human-animal-environment interface.

Infections among Contacts of Patients with Nipah Virus, India.

We conducted a serosurvey of 155 healthcare workers and 124 household and community members who had close contact with 18 patients who had laboratory-confirmed Nipah virus infections in Kerala, India. We detected 3 subclinical infections; 2 persons had IgM and IgG and 1 only IgM against Nipah virus.

Cost-effectiveness of One Health interventions for rabies elimination: a systematic review.

The 'One Health' (OH) approach is the most promising idea in realising the global goal of eliminating canine-mediated human rabies by 2030. However, taking an OH approach to rabies elimination can mean many different things to different people. We conducted a systematic review scrutinizing economic evaluations (EEs) retrieved from MEDLINE OVID, Embase OVID, Global Health OVID, CINAHL EBSCO and ECONLIT EBSCO that used the OH approach with the intent of identifying cost-effective sets of interventions that can be combined to implement an optimal OH-based rabies elimination program and highlight key gaps in the knowledge base. Our review suggests that an optimal OH program to tackle rabies should incorporate mass dog vaccination and integrated bite case management in combination with efficient use of post-exposure prophylaxis along with a shift to a 1-week abbreviated intradermal rabies vaccine regimen in humans. We recommend that future EEs of OH interventions for rabies elimination should be performed alongside implementation research to ensure proposed interventions are feasible and adopt a wider societal perspective taking into account costs and outcomes across both the human health and animal welfare sectors. The systematic review has been registered with PROSPERO.

Contact tracing indicators for COVID-19: Rapid scoping review and conceptual framework.

BACKGROUND: Contact tracing is one of the key interventions in response to the COVID-19 pandemic but its implementation varies widely across countries. There is little guidance on how to monitor contact tracing performance, and no systematic overview of indicators to assess contact tracing systems or conceptual framework for such indicators exists to date. METHODS: We conducted a rapid scoping review using a systematic literature search strategy in the peer-reviewed and grey literature as well as open source online documents. We developed a conceptual framework to map indicators by type (input, process, output, outcome, impact) and thematic area (human resources, financial resources, case investigation, contact identification, contact testing, contact follow up, case isolation, contact quarantine, transmission chain interruption, incidence reduction). RESULTS: We identified a total of 153 contact tracing indicators from 1,555 peer-reviewed studies, 894 studies from grey literature sources, and 15 sources from internet searches. Two-thirds of indicators were process indicators (102; 67%), while 48 (31%) indicators were output indicators. Only three (2%) indicators were input indicators. Indicators covered seven out of ten conceptualized thematic areas, with more than half being related to either case investigation (37; 24%) or contact identification (44; 29%). There were no indicators for the input area "financial resources", the outcome area "transmission chain interruption", and the impact area "incidence reduction". CONCLUSIONS: Almost all identified indicators were either process or output indicators focusing on case investigation, contact identification, case isolation or contact quarantine. We identified important gaps in input, outcome and impact indicators, which constrains evidence-based assessment of contact tracing systems. A universally agreed set of indicators is needed to allow for cross-system comparisons and to improve the performance of contact tracing systems.

COVID-19 in Punjab, India: Epidemiological patterns, laboratory surveillance and contact tracing of COVID-19 cases, March-May 2020.

BACKGROUND: In Punjab, first COVID-19 case was detected on March 5, 2020 followed by multiple clusters. Understanding the epidemiology of reported COVID-19 cases helps decision makers in planning future responses. We described the epidemiological patterns, laboratory surveillance and contact tracing of COVID-19 cases in Punjab. METHODS: We analysed state's COVID-19 data from March-May 2020 to describe time, place and person distribution. We analysed the laboratory surveillance and contact tracing reports to calculate frequency of testing, sample positivity rate (PR) and contacts traced per case. FINDINGS: A total of 2256 cases were reported from March-May 2020 (attack rate 75 cases/million and case fatality rate 2%). Attack rate was higher among males (81 cases/million males) and maximum affected age group was 60-69 years (164∙5 cases/million). Five of 22 districts reported almost half cases in May's first week. Mortality rate was highest among individuals >60 years (six deaths/million) and males (two deaths/million males). Of 45 deaths, 41 reported comorbidities [(hypertension (42%), diabetes (40%)]. COVID-19 testing increased from 46 samples/day (PR: 2%) in March's first week to 4000 samples/day (PR: 2∙5%) by May's end (2752 tests/million). Amritsar conducted 2035 tests/million (highest PR: 6∙5%) while Barnala conducted 4158 tests/million (lowest PR: 1%). For 2256 cases, 19,432 contacts were traced (nine contacts/case) with 11% positivity rate. INTERPRETATION: COVID-19 in Punjab mostly affected males, >60 years of age and individuals with comorbid conditions. Many districts with less testing and contact tracing had higher positivity rate. We recommended to implement and ensure adequate testing and contact tracing in all the districts of Punjab.

Comparing COVID-19 mortality across selected states in India: The role of age structure.

BACKGROUND: Mortality rates provide an opportunity to identify and act on the health system intervention for preventing deaths. Hence, it is essential to appreciate the influence of age structure while reporting mortality for a better summary of the magnitude of the epidemic. OBJECTIVES: We described and compared the pattern of COVID-19 mortality standardized by age between selected states and India from January to November 2020. METHODS: We initially estimated the Indian population for 2020 using the decadal growth rate from the previous census (2011). This was followed by estimations of crude and age-adjusted mortality rate per million for India and the selected states. We used this information to perform indirect-standardization and derive the age-standardized mortality rates for the states for comparison. In addition, we derived a ratio for age-standardized mortality to compare across age groups within the state. We extracted information regarding COVID-19 deaths from the Integrated Disease Surveillance Programme special surveillance portal up to November 16, 2020. RESULTS: The crude mortality rate of India stands at 88.9 per million population (118,883/1,337,328,910). Age-adjusted mortality rate (per-million) was highest for Delhi (300.5) and lowest for Kerala (35.9). The age-standardized mortality rate (per million) for India is (<15 years = 1.6, 15-29 years = 6.3, 30-44 years = 35.9, 45-59 years = 198.8, 60-74 years = 571.2, ≥75 years = 931.6). The ratios for age-standardized mortality increase proportionately from 45 to 59 years age group across all the states. CONCLUSION: There is high COVID-19 mortality not only among the elderly ages, but we also identified heavy impact of COVID-19 on the working population. Therefore, we recommend further evaluation of age-adjusted mortality for all States and inclusion of variables like gender, socio-economic status for standardization while identifying at-risk populations and implementing priority public health actions.