Preventing the Next Pandemic Critical Insights from SARS-CoV-2 Surveillance Systems

Introduction

Preventing the next global pandemic requires a clear understanding of the profound and multifaceted impact of SARS-CoV-2, the virus responsible for COVID-19. Since its emergence, SARS-CoV-2 has infected millions of people worldwide and caused hundreds of thousands of deaths, with rapid and sustained exponential growth observed during early phases of transmission. Beyond its direct health consequences, the pandemic has placed unprecedented strain on healthcare systems, disrupted routine medical services, precipitated widespread economic instability, and intensified public anxiety and social disruption on a global scale. These cascading effects highlight the urgent need to strengthen pandemic preparedness and prevention strategies before the next emerging pathogen reaches a similar scale.

A defining feature of SARS-CoV-2 is its zoonotic origin, reflecting the ability of the virus to cross species barriers and transmit between animals and humans. Since the onset of the pandemic, documented infections have occurred in more than 400 animals across 29 countries, with nearly 300 reported cases in the United States alone. These events underscore the complexity of viral ecology and the critical role of animal reservoirs in sustaining and potentially reintroducing pathogens into human populations. The SARS-CoV-2 experience demonstrates that surveillance limited to human populations is insufficient, particularly when spillover events at the human–animal interface can go undetected until widespread transmission is already underway.

Zoonotic and vector-borne diseases together represent a substantial and growing share of the global infectious disease burden. Vector-borne illnesses alone account for approximately 17 percent of all infectious disease cases worldwide and are responsible for an estimated 700,000 deaths annually. These figures reflect the broader vulnerability of global health systems to pathogens that emerge or reemerge through ecological and environmental pathways. From an economic perspective, the case for prevention is equally compelling. World Bank estimates suggest that comprehensive pandemic prevention efforts would require an annual investment of approximately 11 billion US dollars, whereas the cost of managing an active pandemic can exceed 31 billion US dollars per year. This stark contrast highlights the cost effectiveness of proactive surveillance and prevention compared with reactive crisis management.

Environmental and societal changes play a central role in driving the emergence of novel infectious diseases. Land use modification, deforestation, agricultural expansion, and rapid urbanization increase the frequency and intensity of contact between humans, domestic animals, and wildlife. At the same time, global interconnectedness through travel and trade accelerates the spread of pathogens once spillover occurs. Climate change further amplifies these risks by altering wildlife habitats and geographic distributions. As temperatures rise and ecosystems contract, species are increasingly forced into shared environments, creating multispecies refugia that facilitate viral exchange and cross species transmission. Current evidence indicates that human activity now affects more of the Earth’s surface than remains in a natural or minimally altered state, reinforcing the scale at which anthropogenic factors contribute to pandemic risk.

This article examines key lessons from SARS-CoV-2 surveillance systems to identify actionable strategies for preventing future pandemics. It emphasizes the importance of integrated surveillance approaches that span human, animal, and environmental health, consistent with the One Health framework. By focusing on early detection, data sharing, and coordinated intervention at the human–animal interface, this review aims to outline evidence based pathways for reducing the likelihood that emerging pathogens escalate into global public health emergencies.

SARS-CoV-2 as a Case Study in Zoonotic Spillover

The zoonotic origins of SARS-CoV-2 offer crucial lessons for pandemic prevention. The virus belongs to the Betacoronavirus genus, showing 96% genomic homology to a Yunan bat coronavirus at the whole-genome level [1]. This close relationship underscores bats’ role as likely natural reservoirs for this novel pathogen, though the precise transmission chain remains under investigation.

Wildlife-human interface in Wuhan wet markets

Early COVID-19 cases clustered around the Huanan Seafood Wholesale Market in Wuhan, China, with environmental sampling confirming virus presence in this location. Statistical analysis located the earliest human cases to specific market sections where live wildlife vendors congregated and where virus-positive environmental samples concentrated [1]. Through late 2019, the market sold animals known to be susceptible to SARS-CoV-2 infection [1]. Notably, both lineages A and B of SARS-CoV-2 were detected at the market, with geographic proximity consistent with separate zoonotic events [1].

The market’s structure facilitated animal-human contact, as carcasses and viscera of traded animals littered market areas day and night [1]. Multiple wildlife species were documented at the market, including raccoon dogs, civets, bamboo rats, Malayan porcupines, Amur hedgehogs, and Asian badgers [2]. Moreover, SARS-CoV-2-positive environmental samples contained more DNA from mammalian wildlife than human DNA [2]. Of the wildlife species detected in positive samples, four had previously been implicated in bat coronavirus cross-species transmission: raccoon dogs, masked palm civets, hoary bamboo rats, and Malayan porcupines [2].

Intermediate hosts and viral adaptation pathways

The search for intermediate hosts remains ongoing, with several candidates identified. Genomic analysis suggests pangolins may have served as intermediaries based on 85.5% to 92.4% similarity of viruses found in pangolins to a partial length of the SARS-CoV-2 genome [1]. Additionally, research indicates that minks and rodents are plausible candidate reservoirs [1].

Rats and mice merit particular attention as potential intermediaries due to their widespread distribution in human-adjacent habitats. These rodents were observed in the Huanan market even after its closure on January 1, 2020 [1]. Experimentally, SARS-CoV-2 readily infects and spreads among several mammalian species, demonstrating its host generalist capacity [1]. This ability to adapt to multiple hosts likely facilitated its spillover to humans.

The virus’ entry mechanism relies on the spike protein binding to angiotensin-converting enzyme 2 (ACE2) receptors. The receptor-binding domain (RBD) of SARS-CoV-2 shows higher similarity to pangolin coronaviruses than to bat coronaviruses, suggesting recombination events in its evolutionary history [3].

Comparison with SARS-CoV and MERS-CoV emergence

SARS-CoV-2 shares the Betacoronavirus genus with two other fatal human coronaviruses: SARS-CoV and MERS-CoV [4]. All three evolved in bats, with SARS-CoV-2 showing greater genetic similarity to SARS-CoV (79% identity) than to MERS-CoV (50% similarity) [5].

The emergence patterns show notable parallels. SARS-CoV also spread through wildlife markets, with early cases linked to an animal market in Shenzhen, China [6]. SARS-CoV was detected in palm civets and raccoon dogs sold in markets, with evidence of civet-to-human transmission during a subsequent outbreak in 2003-2004 [6].

Nevertheless, SARS-CoV-2 presents distinct characteristics. Its reproductive number (R0) ranges between 2.0-3.28, exceeding that of SARS (1.7-1.9) and MERS (<1), indicating higher pandemic potential [4]. Conversely, SARS-CoV-2’s case fatality rate (2.3%) is substantially lower than SARS (9.5%) and MERS (34.4%) [4].

A unique feature contributing to SARS-CoV-2’s rapid spread is its ability to transmit before symptom onset [6]. This characteristic, combined with its high transmissibility, enabled the virus to spread globally within months despite unprecedented containment measures.

Environmental Drivers Behind Emerging Zoonoses

Multiple environmental changes accelerate the emergence of zoonotic diseases, creating conditions that foster pathogen spillover from animals to humans. Addressing these drivers is fundamental to constructing effective prevention systems against future pandemics.

Deforestation and habitat fragmentation hotspots

Human activities that alter landscapes, particularly forest conversion and fragmentation, significantly increase the probability of animal-human interactions and subsequent disease transmission [2]. When forests are cleared, species distributions shift dramatically, often increasing contact between wildlife and humans at these newly created edges. Research demonstrates two primary mechanisms through which these landscape alterations promote disease emergence: by enhancing human contact with existing pathogen reservoirs, and by disrupting ecological communities in ways that affect cross-species transmission rates [7].

Species that flourish in human-modified environments often provide greater spillover opportunities based on both their pathogen diversity and increased abundance near human settlements [7]. Approximately 11% of wild terrestrial mammal species serve as hosts for zoonotic viruses, with most harboring only a single such pathogen [7]. Importantly, ecological analyzes reveal that zoonotic host species are generally more resilient to human impacts—they thrive where other species decline [7].

Forest fragmentation creates “island-like” habitats with reduced area, increased isolation, and higher ratios of edge to total area [2]. In the Democratic Republic of Congo, analysis of satellite data predicted that 47% of emerging infectious disease risk across Africa is concentrated there, with another 24% distributed across Cameroon, Gabon, and Mozambique [8]. Such fragmentation particularly affects disease dynamics when agricultural expansion creates crop monocultures adjacent to remnant forest patches [2].

Climate-induced vector migration patterns

Climate change fundamentally alters the geographic distribution of disease vectors—creatures such as ticks, fleas, and mosquitoes that transmit pathogens between hosts [9]. As temperatures increase, these vectors expand their ranges into previously inhospitable regions. For instance, ticks carrying the virus responsible for tick-borne encephalitis have migrated into northern subarctic regions of Asia and Europe [1], whereas in 2019, tropical disease-carrying ticks survived winter months in Germany [1].

Vector population dynamics depend on multiple factors beyond just temperature, including:

• Land use patterns
• Socioeconomic conditions
• Cultural practices
• Access to healthcare
• Human behavioral responses to disease risk [9]

Rising global temperatures extend both the geographic reach of vectors and lengthen transmission seasons [6]. Throughout North America, numerous vector-borne diseases currently pose substantial threats, including Lyme disease, dengue fever, West Nile virus, Rocky Mountain spotted fever, plague, and tularemia [9]. At the same time, pathogens not yet established in the United States, such as chikungunya, Chagas disease, and Rift Valley fever viruses, represent emerging concerns [9].

Illegal wildlife trade and biodiversity loss

The illegal wildlife trade, valued at approximately USD 20 billion annually [5], creates ideal conditions for zoonotic pathogen transmission. This criminal enterprise brings diverse species into close proximity under stressful, unsanitary conditions—essentially creating mixing vessels for pathogens [10]. Between 2011-2020, over 575,000 live animals traded under the CITES convention belonged to species potentially carrying major zoonotic diseases [11]. Expanding the analysis to include animal families associated with disease risk reveals that at least 1.12 million individual animals from these groups were traded during the same period [11].

Wildlife markets specifically amplify disease risks by enabling mixing, amplification, and transmission of pathogens among species [10]. The trade involves multiple phases, each carrying distinct spillover risks: hunting and butchering expose humans to direct pathogen transmission through contact with bodily fluids; transportation forces multiple exotic species into close quarters; and market conditions further concentrate diverse animals in unsanitary environments [5].

Historically, wildlife trade and consumption have triggered numerous disease outbreaks, including HIV-1, Ebola, and monkeypox [10]. For example, the importation of African rodents into the United States led to monkeypox transmission to prairie dogs, which subsequently infected humans [4]. Moreover, the dilution effect theory explains how biodiversity loss increases disease transmission—when species diversity decreases, infection rates between competent hosts and humans intensify due to fewer incompetent hosts to dilute transmission [4].

Surveillance Systems for Early Detection of Zoonotic Threats

Early detection systems represent a vital frontline defense in preventing future pandemics. These sophisticated networks employ various technologies to identify emerging threats before they escalate into widespread outbreaks.

Metagenomic surveillance in high-risk regions

Metagenomic next-generation sequencing (mNGS) has emerged as a powerful tool for pathogen discovery in regions where traditional diagnostics remain limited. This pathogen-agnostic approach allows scientists to detect multiple microorganisms simultaneously without prior knowledge of what might be present. In resource-scarce settings with high biodiversity, mNGS proves especially valuable for identifying disease-causing agents and prioritizing control efforts [12].

Southeast Asia exemplifies a critical surveillance region, where rapid but uneven economic development places 25% of the world’s population at heightened risk [12]. In Cambodia and Laos, laboratory testing for non-malarial fevers remains severely constrained, particularly in rural areas [12]. Field studies in Cambodia have revealed surprising diversity of potential disease vectors, including underappreciated Bartonella species in ticks, mosquitoes, and fleas [12].

Practical applications extend beyond Southeast Asia. In Uganda, researchers utilized mNGS to evaluate samples from febrile children, successfully identifying a novel orthobunyavirus and two previously unknown human rhinovirus C species [13]. Even more telling, during the study period, a lethal HRV-C outbreak occurred among chimpanzees in western Uganda, yet genomic comparison showed little homology between human and chimpanzee sequences—evidence that immediate public health intervention wasn’t necessary [13].

EcoHealth Alliance bat coronavirus screening

For approximately 15 years prior to the COVID-19 pandemic, EcoHealth Alliance conducted crucial surveillance work focused on bat coronaviruses. Their research, led by Peter Daszak, aimed to understand how dangerous viruses jump from bats to humans and to develop tools for diagnostics, treatments, and vaccines [14].

The NIH-funded project “Understanding the risk of bat coronavirus emergence” began in 2014 and was renewed in 2019 after receiving outstanding peer review scores [14]. This initiative included collecting biological samples from wild bats in China and elsewhere to identify high-risk coronaviruses. During its first five years, the project produced vital advances, including genetic sequences of bat coronaviruses later used to test antiviral drugs like remdesivir against COVID-19 [14].

In collaboration with the Wuhan Institute of Virology, EcoHealth researchers collected roughly 15,000 biological samples from bats [14]. Their work identified WIV1, a bat coronavirus capable of directly infecting human cells, demonstrating that SARS-like viruses ready to leap from bats to humans already existed in nature [15].

Limitations of current wildlife virus databases

Current surveillance systems face considerable constraints. Chief among these is the inconsistent reporting of host species, sampling locations, and non-standardized virus naming conventions in public datasets [16]. The Global Early Warning System (GLEWS+) addresses some issues by coordinating information sharing between organizations, but challenges persist in maintaining accurate and timely data from remote regions [17].

Funding shortfalls present another major hurdle. In the United States, federal agencies have taken steps to establish a national wildlife disease surveillance system, yet obstacles related to interoperability and privacy prevent full data integration [18]. Meanwhile, Africa bears over 22% of global zoonotic disease cases despite having only 3% of the global health workforce and less than 1% of financial resources [17].

The SpillOver tool represents an innovative approach to systematically evaluate viruses of wildlife origin for their zoonotic potential, but its effectiveness remains inherently limited by data availability [16]. Hence, expanding large-scale viral detection efforts and improving standardized data reporting remain urgent priorities for effectively preventing the next pandemic.

Lessons from SARS-CoV-2 Surveillance Failures

The COVID-19 pandemic exposed critical weaknesses in global surveillance systems that hampered effective early response. Analysis of these shortcomings provides essential guidance for building more robust detection networks.

Delayed reporting and data suppression in early outbreak

Analysis reveals that reporting delays between symptom onset and case confirmation substantially impacted transmission dynamics. Research demonstrates that removing reporting delays from epidemic data could decrease forecast errors by up to 50% [19]. Cases in their 30s exhibited longer reporting lags than those over 80, while individuals with histories of visiting high-risk areas showed extended delays compared to healthcare workers [20]. In long-term care facilities, outbreaks identified after resident symptomatology had already developed ultimately grew much larger than those caught earlier [21].

Lack of cross-border data sharing protocols

Unfortunately, data-sharing barriers between jurisdictions prevented coordinated response. Current policies restrict federal access to state and local syndromic surveillance data without each jurisdiction’s explicit consent [22]. This fragmentation effectively hampered COVID-19 response by blocking access to vital information needed for broader situational awareness [22]. Throughout 2020, numerous jurisdictions discontinued COVID-19 case notifications, creating critical information gaps [3].

Underfunded zoonotic virus monitoring programs

Consequently, budget constraints undermine prevention efforts. Global disease surveillance requires approximately $800 million annually, yet economic losses from emerging zoonotic diseases have exceeded $200 billion over the past decade [23]. Inadequately funded wildlife trade monitoring enables zoonotic emergence, with CITES explicitly stating pathogen monitoring falls outside its mandate [24]. Furthermore, wildlife researchers face disincentives for reporting potential threats [25].

Building a Global Zoonotic Surveillance Network

Creating effective defense mechanisms against future pandemics requires strategic deployment of surveillance systems at key transmission points. The COVID-19 pandemic has catalyzed renewed interest in establishing robust monitoring networks that can detect potential threats before widespread transmission occurs.

Zoonotic vigilance networks in illegal wildlife markets

Biosurveillance systems focused on wildlife markets represent a critical first line of defense against emerging pathogens. Currently, almost 90% of the 180 recognized RNA viruses harmful to humans are zoonotic in origin [26]. Effective surveillance requires decentralized testing capabilities allowing health professionals to screen pathogens year-round at their source [26]. These systems must prioritize regions with exceptional biodiversity where spillover events are most likely to occur [26].

Integration with One Health and UNEP frameworks

The One Health approach recognizes that human, animal, plant, and environmental health are inextricably linked [4]. This integrated framework enables collaborative efforts across sectors to address the full spectrum of disease control—from prevention to detection and response [4]. The Quadripartite alliance (FAO, UNEP, WHO, WOAH) has developed a Joint Plan of Action outlining three pathways: strengthening policy and financing, enabling organizational development, and enhancing data and knowledge sharing [27].

Funding models inspired by ‘Preventing the Next Pandemic’ book

Sustainable funding remains fundamental for long-term surveillance success. Global disease surveillance requires approximately $800 million annually [28]. Importantly, international funding is justified given the global public good involved in early detection of potential health risks [28]. Innovative financing tools can modify existing aid structures to create predictable funding streams [28].

Conclusion   

The COVID-19 pandemic serves as a stark reminder of our global vulnerability to zoonotic diseases. Evidence from SARS-CoV-2 surveillance confirms how anthropogenic environmental changes dramatically accelerate disease emergence. Deforestation, habitat fragmentation, and wildlife trade create perfect conditions for pathogen spillover, essentially building bridges for viruses to cross from their natural reservoirs to human populations. Additionally, climate change continues to expand the geographic range of disease vectors, thereby introducing pathogens to previously unexposed regions.

Surveillance failures during the early SARS-CoV-2 outbreak revealed critical weaknesses that must be addressed. Delayed reporting, data suppression, inadequate cross-border information sharing, and chronically underfunded monitoring programs collectively hindered effective early response. Therefore, constructing robust early warning systems represents not merely a scientific challenge but an economic imperative, as prevention costs pale in comparison to pandemic management expenses.

Looking forward, several actionable pathways emerge. First, metagenomic surveillance in biodiversity hotspots must become standard practice, allowing detection of novel pathogens before widespread human infection. Second, wildlife markets demand intensified vigilance through decentralized testing capabilities that operate year-round. Third, the One Health framework offers a holistic approach that unites human, animal, and environmental health under a single strategic umbrella.

The COVID-19 catastrophe has paradoxically created unprecedented momentum for pandemic prevention efforts. Nevertheless, this momentum requires transformation into sustainable funding mechanisms and permanent surveillance infrastructure. Without question, countries must recognize zoonotic disease prevention as a global public good deserving of consistent investment rather than cyclical crisis-driven funding.

Throughout history, humanity has faced devastating pandemics. However, modern science now provides tools to detect and mitigate threats before they escalate. The next pandemic remains inevitable only if we fail to apply these lessons. Our collective future depends on building systems that can rapidly identify emerging pathogens at the human-animal interface and respond before widespread transmission occurs. Thus, preventing the next pandemic requires not just scientific innovation but also political will, international cooperation, and sustained financial commitment to global health security.

Key Takeaways

The COVID-19 pandemic revealed critical gaps in global surveillance systems while highlighting the urgent need for proactive zoonotic disease prevention strategies.

• Environmental destruction drives pandemic risk: Deforestation, habitat fragmentation, and illegal wildlife trade create ideal conditions for pathogen spillover from animals to humans.
• Early detection systems save lives and money: Pandemic prevention costs $11 billion annually versus $31 billion for managing active outbreaks, making surveillance a smart economic investment.
• Wildlife markets need constant monitoring: Metagenomic surveillance in biodiversity hotspots and wildlife trading centers can detect novel pathogens before human transmission occurs.
• Data sharing failures cost lives: Delayed reporting and lack of cross-border information protocols during COVID-19 hampered global response efforts by up to 50%.
• One Health approach is essential: Integrating human, animal, and environmental health surveillance creates comprehensive defense against emerging zoonotic threats.

The next pandemic is preventable only if we apply these lessons through sustained funding, international cooperation, and robust surveillance infrastructure at the human-animal interface.

Frequently Asked Questions:   

FAQs

Q1. What are the main environmental factors contributing to the emergence of zoonotic diseases? The main environmental factors include deforestation, habitat fragmentation, climate change, and illegal wildlife trade. These activities increase human-animal contact, alter vector migration patterns, and create conditions that facilitate pathogen spillover from animals to humans.

Q2. How effective were the surveillance systems during the early stages of the COVID-19 outbreak? Surveillance systems during the early stages of COVID-19 had significant shortcomings. There were delays in reporting, instances of data suppression, lack of cross-border data sharing protocols, and underfunded zoonotic virus monitoring programs, which collectively hindered effective early response to the outbreak.

Q3. What is the One Health approach and why is it important for preventing future pandemics? The One Health approach is an integrated framework that recognizes the interconnectedness of human, animal, plant, and environmental health. It’s crucial for pandemic prevention as it enables collaborative efforts across sectors to address the full spectrum of disease control, from prevention to detection and response.

Q4. How can metagenomic surveillance help in early detection of zoonotic threats? Metagenomic surveillance, especially in high-risk regions, allows for simultaneous detection of multiple microorganisms without prior knowledge of what might be present. This pathogen-agnostic approach is particularly valuable in resource-scarce settings with high biodiversity, enabling early identification of potential disease-causing agents.

Q5. What are the economic implications of investing in pandemic prevention? Investing in pandemic prevention is economically beneficial. While global disease surveillance requires approximately $800 million annually, the economic losses from emerging zoonotic diseases have exceeded $200 billion over the past decade. Prevention costs ($11 billion yearly) are significantly lower than managing active pandemics ($31 billion annually), making it a smart economic investment.

References:  

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