On 28 March 2021 Myanmar security forces shot protesters in Yangon city. Some sought refuge in the hospital where soldiers and police followed them and opened fire. Unfortunately, this kind of violence on health care is all too common in contexts affected by armed conflict. Since the full-scale invasion of Ukraine in 2022, the World Health Organization (WHO) Surveillance System for Attacks on Health Care (SSA) has verified over 715 attacks on health. A Safeguarding Health in Conflict Coalition (SHCC) and Insecurity Insight review of five years of data on attacks found ‘more than 4,000 unique incidents of violence against health care in situations of armed conflict—on average more than two incidents a day.’ These attacks threaten health workers, individual health outcomes for patients and conflict-affected populations, and jeopardise access to health services.
The question in the title may seem relatively straightforward. Scholarly and policy analysis about attacks on health care call for more data and better monitoring to document and understand the issue and to ensure accountability (see here and here). These numbers have gotten headlines about Ukraine and COVID-19, helping to raise awareness about these attacks.
But do numbers do more than raise awareness? What do we know about their influence? Put another way, what is the relationship between data, often numbers, and changes in policy or behaviour? Scholars have examined the efficacy of transnational advocacy and decision-making but few have examined the specific role of data in these processes.
In a recent publication, my colleague Róisín Read and I consider the relationship between data and change, as part of a broader effort to research the impact of attacks on health care. In our open-access article, we argue that data about attacks on healthcare are indeed necessary for understanding the scope of the problem and for raising awareness. But the continued occurrence of attacks demonstrates that data are insufficient in creating normative, policy, or behavioural change. To investigate the complex and potential role of data in these processes, we focus on two pathways for change. We call the first pathway ‘operational change,’ designed to prevent or mitigate the impact of attacks on health. The second refers to normative change, often pursued via transnational advocacy aiming to achieve a reduction in the frequency of attacks. The former operates at the level of those affected by attacks, while the latter works at the level of those perpetrating attacks.
Our investigation highlights the institutional, political, and social contexts in which data are produced and used, and how these contexts can be as significant as the evidence they provide for decision-making and advocacy efforts. We find that many issues impact on the role of data related to policy or programmatic change, from the technical (eg related to standards and terminology) to issues of bias and the social or institutional networks that shape data collection and use. To be useful, data should be collected with a clear purpose that is meaningful for those collecting, analysing, and using the data. Moreover, the political context impacts on the framing of data and the incentives to under- or overreport, whether about harms or disease. Even the terminology used in collecting data can be a point of political contention. As we write, ‘Data are never neutral; they privilege particular, subjective realities that are especially contested in fractious political contexts.’
Additionally, at the levels of operational and normative change, the role of personal and institutional relationships are crucial. For instance, individuals and organizations bring existing biases and frames of reference to bear on the data they encounter. As a result, data that challenge preconceptions are likely to require a higher burden of proof to become credible. Yet personal and institutional connections also strengthen trust in and interpretation of data. This highlights the crucial role of broad-based networks, which can help to build trust in the underlying data. In doing so, these connections enhance the potential for data to influence change.As academics do, we conclude with a call for more research to investigate the often positive but non-linear role of data in change processes. While our specific focus was on the relationship between data attacks on health, we hope these insights assist other efforts to affect decision-making or create behavioural, policy, or normative change.