July 19, 2016

We Need Global, Standardized Reporting for Disease Outbreaks: The Case of H1N1

Improving reporting accuracy could save resources, lives


By Abhijit Duggal, MD


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Accurate mortality reporting during disease outbreaks is vitally important. Conversely, inaccurate reporting can lead to overmobilization of health care activity and therefore wasted resources, or undermobilization and an inadequate response.

Take for instance the Ebola outbreak in West Africa in 2014. Initial estimates of mortality were placed at 70 to 80 percent based on the first outbreak reports. But as more detailed reporting was analyzed, the average case fatality rate was closer to 50 percent. Which of these numbers offers policymakers an accurate way to determine resource allocation?

To explore this conundrum, our multisite research team conducted a meta-analysis of 226 studies from 50 countries on the influenza A (H1N1) pandemic of 2009-2010. We found that overreporting of mortality may occur when studying populations in narrow time periods or in specific geographical regions.

We determined that mortality reporting for outbreaks and pandemics can vary substantially, depending upon patient characteristics selected, number of patients described and the region and economic status of the outbreak location. Outcomes from a relatively small number of patients from specific regions may lead to biased estimates of outcomes on a global scale.

Early reports may be skewed

When a disease outbreak occurs, first reports generally focus on the sickest patients. For instance, in the U.S., initial reports on H1N1 pegged mortality close to 50 percent, and later 40 to 60 percent. Australia produced the first nationwide report on H1N1 about six months into the pandemic. By including patients who were less severely ill and over a longer timeframe, Australian researchers calculated aggregate mortality rate at 11 percent. Population-based factors most likely came into play, but is difficult to evaluate their impact due to the inconsistency in reporting of these variables. It is also difficult to study these variables as the original data worldwide was not of high enough quality to report these findings with full confidence.


Reported mortality associated with 2009 Influenza A (H1N1) associated critical illness.


We describe the mortality based on temporal (early, late and prolonged enrollment), study (study size, single center compared to multicenter and adults compared to pediatrics), and the geographic location and socioeconomic development from the included studies. The black squares represent the point estimate and 95% confidence intervals (CIs) around the mortality for each subgroup. The black diamond is the summary or overall combined estimate of mortality associated with the 2009 Influenza A (H1N1) pandemic.

First wave versus second wave mortality, and critical illness

Mortality for the first wave of H1N1 was not significantly higher than the second wave (P = 0.66). However, there was substantial variability in reported mortality among subgroups of patients based on the type of illness they were experiencing: unselected critically ill adults (27% [95% CI 24–30]), acute respiratory distress syndrome (37% [95% CI 32–44]), acute kidney injury (44% [95% CI 26–64]), and critically ill pregnant patients (10% [95% CI 5–19]). Early reports during pandemics should refrain from reporting on specific populations during narrow timeframes, as they can overreport the mortality associated with the disease outbreak.

Informing public health policy

We hope that findings from our study help guide public health policy and responses and inform clinical decisions during future outbreaks of diseases such as seasonal or avian influenza, Middle East respiratory syndrome, coronavirus or Ebola. We need to distinguish between early and late outcomes, geographical regions and outbreak waves. Politics affect decision-making, too. During outbreaks, public policy makers may feel pressured “to do something.” Decisions related to resource allocation during disease outbreaks should be made based on temporal, geographic and patient-related factors and not on a knee-jerk reaction to initial reports. But we need to be mindful that policy decisions based on early reports of a disease outbreak from specific geographical regions might be inaccurate.

Reporting disease outbreaks in a consistent manner around the world is a challenging task. We lack standard definitions, forms and data collection procedures. In this study, my colleagues and I conclude that a standardized global approach to reporting outbreaks and pandemics will provide us more accurate estimates of morbidity and mortality associated with new diseases and provide the most valid information upon which to base current and future research, clinical care and health systems responses.


Dr. Duggal is a staff physician in the Department of Critical Care, Respiratory Institute, and

Associate Program Director, Critical Care Fellowship.

Read more Consult QD posts from Cleveland Clinic Respiratory Institute.

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