Data: A Critical Defence in Pandemic Response

Epidemiologist and CanWaCH CEO, Dr. Helen Scott, follows the data and shows how it is used to help combat a pandemic

The COVID-19 pandemic exemplifies why tracking and gathering reliable data — that can be analyzed and applied to make decisions — is imperative in public health.

Public health officials’ pandemic toolbox includes public awareness, social distancing, personal hygiene, and containment through quarantine of those potentially exposed to the virus. Yet an equally important tool of defence during a pandemic is a reliable system for communities to quickly report accurate data about the outbreak so that provincial and federal officials can rapidly identify and implement the most effective interventions.

The Data Pathway

National surveillance is a critical mitigation measure. Initially, surveillance systems rapidly detect cases and assess community transmission. Traditional public health approaches rely on some detective work, including tracing and tracking individuals who have been in close contact with an infected individual. Scientists can track small changes in the virus’ genetic code as it spreads from person to person. These changes act like genetic fingerprints of the virus, helping researchers to chart its movements in near real time.

Early on in an outbreak, when all community-based transmissions can be traced back to an individual — called patient zero — that is a good sign that the virus is well contained. Once the virus is spreading without a clear link to the source of the disease, tracking patient zero becomes less useful for containment purposes and enhanced surveillance measures and multiple surveillance mechanisms will ensure broad coverage to identify chains of transmission.

As an epidemic expands, surveillance monitors the intensity, geographical spread, and the impact of the epidemic on the population and healthcare systems. Robust surveillance measures include a case database that is accurate, transparent, and accessible to decision makers. Ideally, governments also have access to lists of trained personnel, from local leaders to global experts, who can advise on actions, as well as lists of supplies to be stockpiled or redirected in emergency.

Supplementing the surveillance, mathematical modeling can project how a disease might progress. Models are like a weather forecast: researchers use mathematical equations to project disease outcomes, taking into consideration uncertainties and incomplete data. The debate in approach in the United Kingdom over the past week has seen scientists call for the government to share the models upon which they are driving their decisions. Mathematical models are not crystal balls – with a wide range of estimates, these models can seem like guesswork – but they are an important tool to help make decisions based on the available evidence.

Reliable and valid data is essential across the global health ecosystem, whether in response to a pandemic or towards accountability in global women and children’s health programming.

Gathering, applying and using data to drive decision-making is foundational to CanWaCH’s work. While the context for our work may not seem as urgent, the numbers remain staggering. Globally, every two minutes one woman dies from pregnancy or childbirth complications. And every day 15,000 children die of preventable causes around the world.

The collective work of our partnership to improve global health and gender equality requires timely, reliable, and accessible health information and data to better track progress, to reveal inequities through more disaggregated data, and to focus on improving information for better results.

The COVID-19 pandemic has brought the need for good data into our living rooms as we follow the daily numbers and reports. And, it illustrates why CanWaCH and our members continue to take steps to get better at measuring results, tracking resources and reporting progress.