Six steps for improving disease surveillance in underserved remote rural communities

A global team of scientists has developed a framework for extending disease surveillance into remote areas of low- and middle-income countries (LMICs), an essential step towards improving health security in the world’s most vulnerable regions. The team includes scientists from the Smithsonian Institution, the University of Minnesota, Saint Louis Zoo, the Field Museum, the International Livestock Research Institute (ILRI), Mpala Research Centre, the Kenya Wildlife Service (KWS), the Peregrine Fund, the University of Washington, and Yale University. Their research appears as a Viewpoint in the April 2022 edition of The Lancet Global Health under the title “Strengthening global health security by improving disease surveillance in remote rural areas of low-income and middle-income countries”.

The COVID-19 pandemic has highlighted the need to strengthen global disease surveillance. While surveillance systems have advanced considerably in LMICs over the last two decades, they frequently fail to reach remote and rural communities, where approximately half of all people in LMICs live. Given the frequent contact these communities have with livestock and wildlife and the regular movement of people and animals between rural and urban areas and across national borders, inadequate surveillance within these areas poses a major threat to global health security and pandemic preparedness. “A synergistic surveillance approach in LMICs offers a great opportunity to address pandemics early, saving human lives and preventing losses in wildlife and livestock”, says Kenya Wildlife Service veterinarian and co-author Dr Mathew Mutinda.

Created by an interdisciplinary team with expertise ranging from wildlife conservation to public health and social responsibility, the six-step framework represents one of the first efforts to outline how a holistic disease surveillance approach can be implemented even in the most remote of regions. “Bringing together researchers that tackle zoonotic disease problems in different ways allowed us to cover and find solutions to a broad range of challenges associated with conducting zoonotic disease surveillance in remote rural settings, in a way that is linked to existing surveillance systems”, says Smithsonian Postdoctoral Fellow and lead author Dr Katherine Worsley-Tonks.

Utilizing pastoral and smallholder communities in Kenya as a case study, the framework can be adapted to remote rural communities around the world at high risk of zoonotic disease and marginalized from healthcare services. “Incorporating remote and marginalized communities in comprehensive disease surveillance systems, not only brings closer the reality of evidence-informed human and animal health management, pandemic preparedness and household livelihood security, but also enhances health justice”, says University of Minnesota research scientist and co-author Dr George Omondi.

The first step in the framework is to engage all relevant stakeholders. Successful disease surveillance requires interdisciplinary collaboration between animal and human health workers, which can be achieved through local level working groups that bring together representatives from different sectors to discuss zoonotic disease outbreak prevention.

Once the relevant stakeholders are in place, the next step is to establish syndromic surveillance – a health system designed to detect disease outbreaks via early warning signs rapidly – and the key to this is ensuring that people living in remote rural areas lead this effort. Mobile-phone applications are a valuable tool as they can overcome barriers related to remoteness and facilitate information sharing between animal and human health workers and wildlife rangers to gather context-specific information on zoonotic diseases. “Bringing more people from local communities into a surveillance system will be a huge boost to detecting or preventing the next pandemic. Those communities living and working in remote areas where people, livestock and wildlife share land and water are best placed to be part of an early-warning system as they have immense, direct knowledge of their landscape.” says Mpala Research Centre executive director, Princeton University research scholar and lecturer, and co-author Dr. Dino Martins.

To maximize their effectiveness, syndromic surveillance systems should be accompanied by increased clinical and diagnostic capacity—the next two steps in the framework. This can be accomplished by establishing training programs in rural communities that teach clinicians to adequately respond to syndromic data by practising One Health, adapting to different disease scenarios, and identifying emerging outbreaks. Training efforts should also focus on improving the availability of diagnostic tests and strengthening front-line workers’ interpretations of results.

The framework's final two steps seek to integrate disease surveillance into national and global efforts in remote rural areas. This involves building systems, such as an open-source online database for communicating and sharing data across geographical scales. The final step is to engage national governments and international stakeholders to transform data outputs into actionable interventions and policies.

“Investment in robust but simple disease surveillance approaches is acutely needed in remote areas of low resource settings to improve health outcomes”, says ILRI research scientist and co-author Dr Dishon Muloi. Ultimately, the framework provides essential guidance for improving zoonotic disease surveillance in remote rural areas in Kenya and worldwide, efforts that could prove vital in preventing the next global pandemic.