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Structural failures in surveillance infrastructure and zoonotic emergence increase global pandemic risksGlobal health experts identify gaps in pandemic and disease tracking

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Key Takeaway
Recognize that fragmented surveillance infrastructure and zoonotic emergence increase global pandemic risks.

This narrative review synthesizes current evidence regarding infectious disease threats, specifically focusing on zoonotic emergence, antimicrobial resistance, and the expansion of climate-sensitive diseases. The authors argue that these factors have intensified the risk of future pandemics. The review highlights that current surveillance infrastructure suffers from structural failures, including fragmented laboratory networks, inequitable genomic capacity, and a lack of integration across human, animal, and environmental systems.

Regarding technological interventions, the review notes that AI-enabled forecasting, wastewater monitoring, and social media surveillance show technical promise. However, these tools are accompanied by risks regarding data bias and governance gaps. The synthesis emphasizes that current systems are often insufficient to address the scale of emerging threats.

Clinical and policy implications focus on the need for redistributive investment in One Health integration, regional genomic platforms, and community-based surveillance. These measures are proposed to address the identified structural weaknesses in global pandemic preparedness. The review serves as a synthesis of evidence and policy reports rather than a primary clinical trial.

How this fits prior evidence

This narrative review extends prior findings regarding the risks of zoonotic spillover driven by cultural practices and climate shifts. It also builds upon evidence that cross-sectoral collaboration and technological integration are essential for improving zoonotic disease detection. While previous reports noted that climate change drives increased frequency of vector-borne diseases, this review highlights the specific structural failures in the infrastructure required to monitor such expansions.

The world is facing a growing list of threats from diseases that jump from animals to humans, the rise of drug-resistant germs, and the spread of illnesses linked to a changing climate. While these risks are increasing, our current systems for watching these threats are often broken or disconnected.

Experts found that our tracking systems suffer from structural failures. These include fragmented laboratory networks and unequal access to the technology needed to map germs. Because our systems for tracking human, animal, and environmental health are not well integrated, it is harder to catch a new outbreak before it spreads globally.

New digital tools like artificial intelligence and wastewater monitoring show promise for spotting risks early. However, these technologies come with their own hurdles, such as data bias and gaps in how they are managed. To improve global safety, experts suggest investing more in shared regional platforms and community-based monitoring to close these gaps.

What this means for you:
Fragmented tracking systems and unequal resources make it harder to stop the next global disease outbreak.

Common questions

What are the main risks for future pandemics?

The main risks include diseases jumping from animals to humans, the rise of antimicrobial resistance, and the spread of diseases caused by climate changes. These threats have intensified since the COVID-19 pandemic, making global preparedness more urgent than ever before.

Why is our current disease tracking system weak?

Current systems face structural failures, such as fragmented laboratory networks and unequal access to genomic tools. Because human, animal, and environmental health systems are not well integrated, it is difficult to track and stop diseases effectively.

Can technology help track these diseases?

Digital tools like artificial intelligence, wastewater monitoring, and social media tracking show promise for spotting threats. However, these tools also bring risks, such as data bias and gaps in how the information is managed and governed.

Study Details

Study typeSystematic review
EvidenceLevel 1
PublishedSep 2026
View Original Abstract ↓
The COVID-19 pandemic exposed profound weaknesses in global infectious disease surveillance yet, in its aftermath, pandemic-prone threats have intensified rather than receded. This narrative review synthesizes contemporary evidence on three converging drivers of pandemic risk zoonotic emergence, antimicrobial resistance, and climate-sensitive disease expansion and examines how structural failures in surveillance and global health governance amplify their impact. Drawing on recent epidemiological analyses, policy reports, and One Health evaluations, the review maps post-COVID surges in zoonotic outbreaks, drug-resistant infections, and vector and water-borne diseases, and links these trends to fragmented laboratory networks, inequitable genomic capacity, and weak integration across human, animal, and environmental systems. It further interrogates the geopolitical and socioeconomic determinants of vulnerability, including conflict-related surveillance collapse, vaccine inequity, and the political economy of pandemic financing. Emerging digital tools from AI-enabled forecasting to wastewater and social media surveillance are assessed not only for their technical promise but also for risks related to data bias, extractives, and governance gaps. The review argues that without redistributive investment in One Health integration, regional genomic platforms, community-based surveillance, and enforceable IHR-based accountability, the world will continue to detect converging threats late and respond inequitably, leaving pandemic preparedness structurally fragile in the post-COVID era.
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