Preventing Pandemics via International Development: A Systems Approach

Tiffany Bogich and colleagues find that breakdown or absence of public health infrastructure is most often the driver in pandemic outbreaks, whose prevention requires mainstream development funding rather than emergency funding

Wild animal and zoonotic disease risk management and regulation in China : examining gaps and One Health opportunities in scope, mandates, and monitoring systems

Emerging diseases of zoonotic origin such as COVID-19 are a continuing public health threat in China that lead to a significant socioeconomic burden. This study reviewed the current laws and regulations, government reports and policy documents, and existing literature on zoonotic disease preparedness and prevention across the forestry, agriculture, and public health authorities in China, to articulate the current landscape of potential risks, existing mandates, and gaps. A total of 55 known zoonotic diseases (59 pathogens) are routinely monitored under a multi-sectoral system among humans and domestic and wild animals in China. These diseases have been detected in wild mammals, birds, reptiles, amphibians, and fish or other aquatic animals, the majority of which are transmitted between humans and animals via direct or indirect contact and vectors. However, this current monitoring system covers a limited scope of disease threats and animal host species, warranting expanded review for sources of disease and pathogen with zoonotic potential. In addition, the governance of wild animal protection and utilization and limited knowledge about wild animal trade value chains present challenges for zoonotic disease risk assessment and monitoring, and affect the completeness of mandates and enforcement. A coordinated and collaborative mechanism among different departments is required for the effective monitoring and management of disease emergence and transmission risks in the animal value chains. Moreover, pathogen surveillance among wild animal hosts and human populations outside of the routine monitoring system will fill the data gaps and improve our understanding of future emerging zoonotic threats to achieve disease prevention. The findings and recommendations will advance One Health collaboration across government and non-government stakeholders to optimize monitoring and surveillance, risk management, and emergency responses to known and novel zoonotic threats, and support COVID-19 recovery efforts

Using network theory to identify the causes of disease outbreaks of unknown origin.

The identification of undiagnosed disease outbreaks is critical for mobilizing efforts to prevent widespread transmission of novel virulent pathogens. Recent developments in online surveillance systems allow for the rapid communication of the earliest reports of emerging infectious diseases and tracking of their spread. The efficacy of these programs, however, is inhibited by the anecdotal nature of informal reporting and uncertainty of pathogen identity in the early stages of emergence. We developed theory to connect disease outbreaks of known aetiology in a network using an array of properties including symptoms, seasonality and case-fatality ratio. We tested the method with 125 reports of outbreaks of 10 known infectious diseases causing encephalitis in South Asia, and showed that different diseases frequently form distinct clusters within the networks. The approach correctly identified unknown disease outbreaks with an average sensitivity of 76 per cent and specificity of 88 per cent. Outbreaks of some diseases, such as Nipah virus encephalitis, were well identified (sensitivity = 100%, positive predictive values = 80%), whereas others (e.g. Chandipura encephalitis) were more difficult to distinguish. These results suggest that unknown outbreaks in resource-poor settings could be evaluated in real time, potentially leading to more rapid responses and reducing the risk of an outbreak becoming a pandemic

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

A qualitative study of zoonotic risk factors among rural communities in southern China

Strategies are urgently needed to mitigate the risk of zoonotic disease emergence in southern China, where pathogens with zoonotic potential are known to circulate in wild animal populations. However, the risk factors leading to emergence are poorly understood, which presents a challenge in developing appropriate mitigation strategies for local communities.Residents in rural communities of Yunnan, Guangxi and Guangdong provinces were recruited and enrolled in this study. Data were collected through ethnographic interviews and field observations, and thematically coded and analysed to identify both risk and protective factors for zoonotic disease emergence at the individual, community and policy levels.Eighty-eight ethnographic interviews and 55 field observations were conducted at nine selected sites. Frequent human–animal interactions and low levels of environmental biosecurity in local communities were identified as risks for zoonotic disease emergence. Policies and programmes existing in the communities provide opportunities for zoonotic risk mitigation.This study explored the relationship among zoonotic risk and human behaviour, environment and policies in rural communities in southern China. It identifies key behavioural risk factors that can be targeted for development of tailored risk-mitigation strategies to reduce the threat of novel zoonoses

Bat Severe Acute Respiratory Syndrome-like coronavirus WIV1 encodes an extra accessory protein, ORFX, involved in modulation of the host immune response

Bats harbor severe acute respiratory syndrome (SARS)-like coronaviruses (SL-CoVs) from which the causative agent of the 2002-2003 SARS pandemic is thought to have originated. However, despite the fact that a large number of genetically diverse SL-CoV sequences have been detected in bats, only two strains (named WIV1 and WIV16) have been successfully cultured in vitro. These two strains differ from SARS-CoV only in containing an extra open reading frame (ORF) (named ORFX), between ORF6 and ORF7, which has no homology to any known protein sequences. In this study, we constructed a full-length cDNA clone of SL-CoV WIV1 (rWIV1), an ORFX deletion mutant (rWIV1-ΔX), and a green fluorescent protein (GFP)-expressing mutant (rWIV1-GFP-ΔX). Northern blotting and fluorescence microscopy indicate that ORFX was expressed during WIV1 infection. A virus infection assay showed that rWIV1-ΔX replicated as efficiently as rWIV1 in Vero E6, Calu-3, and HeLa-hACE2 cells. Further study showed that ORFX could inhibit interferon production and activate NF-κB. Our results demonstrate for the first time that the unique ORFX in the WIV1 strain is a functional gene involving modulation of the host immune response but is not essential for in vitro viral replication. IMPORTANCE Bats harbor genetically diverse SARS-like coronaviruses (SL-CoVs), and some of them have the potential for interspecies transmission. A unique open reading frame (ORFX) was identified in the genomes of two recently isolated bat SL-CoV strains (WIV1 and -16). It will therefore be critical to clarify whether and how this protein contributes to virulence during viral infection. Here we revealed that the unique ORFX is a functional gene that is involved in the modulation of the host immune response but is not essential for in vitro viral replication. Our results provide important information for further exploration of the ORFX function in the future. Moreover, the reverse genetics system we constructed will be helpful for study of the pathogenesis of this group of viruses and to develop therapeutics for future control of emerging SARS-like infections

Figurative description of the multi-scale, multi-step process of pandemic emergence.

<p>Pandemic impact is highest when diseases are transmitted rapidly from human to human, and spread via travel and trade networks (A). At that point, their impact is greatest in developed countries, with economic dependence on globalized travel and trade (e.g., SARS). However, most emerging diseases do not reach this stage, and emerge in localized outbreaks, often small and contained (B, red spikes), or spillover repeatedly from animals (B, green line). Here, control is most effective at the countries of origins that are often developing countries, where breakdown of public health measures exacerbates human-to-human spread. Prior to localized outbreaks of zoonoses, perturbations in the environment lead to spillover of pathogens from one animal species to another or their range expansion (C, green circles). The most effective pandemic prevention at this early stage would be via measures that target the underlying causes of disease emergence.</p

The number of outbreaks by driver, with the subplot representing the subdrivers within the category “breakdown of public health measures” (Table S3).

<p>The number of outbreaks as taken from the Chan et al. <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001354#pmed.1001354-Chan1" target="_blank">[6]</a> dataset of DON reports attributed to different ecological, socioeconomic, and political drivers. There are some inherent uncertainties in the reported set of outbreaks, and biases in the reporting of disease outbreaks have been discussed previously <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001354#pmed.1001354-Jones1" target="_blank">[4]</a>,<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001354#pmed.1001354-Chan1" target="_blank">[6]</a>. As the breakdown of public health measures accounted for the greatest number of outbreaks, for that driver, three additional subcategories were examined, including inadequate sanitation and hygiene, poor immunization coverage, and vector-borne and zoonotic disease control measures (e.g., bednets and improved drainage to eliminate standing water). Drivers associated with fewer than ten events (which included “human susceptibility to infection,” “land use changes,” and “medical industry changes”) were combined into the single category “other.” Outbreak events with unassigned or uncertain drivers (e.g., disagreement between sources) were labeled as “unspecified.”</p