Humanitarian information systems typically provide analysis to predict crisis, assess needs, direct program resources, and assess short- to medium-term effects of programs. But much of this information is “chunky”—a single estimate of “needs,” for example, can be expected to direct resources and programming for up to a full year (IASC 2020). A single early warning scenario might be expected to provide information about potential hazards and the exposure of population to the ill-effects of that hazard for three to four months. And almost by definition, early warning analyses are grounded in known and likely hazards, “population in need” (PIN) figures are based on the impacts of known shocks, and program resources are (or should be) allocated on the basis of known and projected PIN figures. There have long been questions about the timeliness of humanitarian information and especially about the extent to which information initiates appropriate and timely actions (Buchanan-Smith and Davies 1995; Bailey 2012;
Lentz et al. 2020). And there have always been concerns that circumstances can change in shorter time periods than standard humanitarian analysis procedures can pick up, so interest in real-time monitoring (RTM) as a component of humanitarian information systems has increased for at least the past decade or so (FSNAU 2015).
But with the arrival of COVID-19 in 2020, an altogether different situation arose that dramatically increased the pressure for a different kind of monitoring. While the mainstay of humanitarian information systems has long been food security and nutrition information (especially the former), the COVID-19 pandemic has been first and foremost a public health crisis. Public health information systems exist, and indeed warnings of the possibility of something like COVID-19 have been around for some time. However, a variety of factors minimized the transmission of warnings in 2020 between public health information systems and humanitarian actors. First, food security and nutrition information systems had been focused on the usual drivers and outcomes; a pandemic was not in anyone’s most-likely scenario. Second, the knock-on effects of the pandemic spread quickly to other sectors, particularly food security, livelihoods, and nutrition, but in ways that information systems weren’t necessarily set up to track—with both supply- and demand-side impacts, some of which were novel and difficult to estimate. Third, and perhaps most critically, pandemic-control methods (particularly lock-downs and social distancing) prevented some of the standard information collection and analysis procedures—or at least made them much more difficult and costly.
System managers innovated quickly—physically-distanced information collection methods were developed or pre-existing initiatives expanded, remote analyses took place, and new factors were taken into consideration (FEWS NET 2020; IPC 2021). But methods that relied on close physical contact (such as anthropometric surveys) faced greater difficulties in adapting. The rapidly changing conditions made it clear that the time frames for standard humanitarian analysis could not keep up with the pace of change in the pandemic or its knock-on effects.
The impacts of the pandemic came on top of pre-existing confusion about some forms of humanitarian information and about what kinds of information were appropriate for what kinds of decisions and actions (Maxwell and Hailey 2020). Perhaps worst of all, the pandemic damaged the global economy significantly, leading to shrinking economic output in donor countries at a time when there were significant demands for domestic relief programs in those countries—all leading to shrinking budgets for humanitarian action at a time when needs were certainly expanding (WFP/FAO 2020; OCHA 2021).
Already significantly challenged, information systems were being relied on to inform crucial decisions about resource allocation, leading to more demand than ever for precise, rapidly updated information on crises. The need for real-time information only increased as it became clear that, because of the global economic downtown resulting from the pandemic, the funding base was also going to shrink compared to rising needs.