Preparedness efforts for health threats: the gap between detection and action

The World Health Organisation (WHO) was highly criticised for its delay in declaring Covid-19 as a public health emergency of international concern (PHEIC) via social media and a public investigation, (see the final report of the Independent Panel on Pandemic Preparedness and Response). But would earlier detection have necessarily resulted in an earlier and/or better response? In this article, Claudia Fernandez de Cordoba Farini, Head of Health Warnings R&I at the UCL Warning Research Centre, looks at the gap between detection and action concerning preparedness efforts for health threats.

Introduction

Warning systems research and preparedness actions for epidemics are often centred around improving surveillance, detection and forecasting of health threats. These priorities often rely on the use and improvement of technologies, and quantitative analysis to monitor, model and conduct risk assessments of health threats. Efforts and research towards these objectives are wide-ranging, both at the international and national level.

Numerous organisations and systems exist that monitor social media, or rely on electronic reporting systems to detect health threats, including:

• Global Public Health Intelligence Network (see Mykhalovskiy and Weir 2006).
• Health Map (see Freifeld, et al., 2008 and Bhatia et al., 2021).
• Epitweetr (see Espinosa et al., 2021).
• Promed-Mail (see Madoff 2014).
• China Infectious Diseases Automated-Alert and Response System (CIDARS) (see Yang et al., 2017).
• Risk Assessment and Early Warning (RAEW) units in Netherlands (see Vlieg et al., 2017).

Efforts towards improving those systems in developing countries are also increasing e.g., Yemen’s electronic disease early warning system (Dureab et al., 2020) and India’s Electronic Emergency Medical Service Data for Early Warning of Infectious Diseases (Pilot et al., 2017).

Moreover, there is also significant research on systems that leverage more advanced technologies, such as satellite data, wireless and radio networks, data mining, and integration technology, to identify and respond to a disease outbreak (see Chronaki et al., 2007; Qu and Chandra Wickramasinghe 2020; and Guo et al., 2020).

The focus on surveillance and detection is also apparent as part of the International Health Regulations (IHR); the principal governing instrument to mitigate and respond to pandemics (see Kamradt-Scott 2019). Among the fifteen different categories evaluated in countries’ 2022 self-assessment to meet the objectives set by the IHR; the highest average score was in the capacity for surveillance to detect public health risks at 80%. In contrast, scores for other categories such as risk communication and community engagement (67%) or infection prevention and control (60%), were significantly lower (see Razavi, et al., 2021).

The push towards improving surveillance and forecasting of public health threats often relies on the assumption that earlier detection will result in improved warning systems and responses for health threats. However, based on case studies from the SARS and Covid-19 pandemics, Ebola epidemics, as well as a range of other natural hazards; that assumption does not often hold true.

The following case studies, examine the gap between detection and action, focusing on political and economic barriers, as well as risk communication, in order to generate key insights as to how we can enhance warning systems and preparedness actions for health threats.

SARS, 2002: the gap due to bureaucracy and a lack of transparency and accountability mechanisms

The earliest case of SARS is thought to have occurred in Foshan municipality, Guangdong Province, China in November 2002. This unknown disease became a concern for Chinese health personnel as early as mid-December 2002 (see Huang 2004). The Ministry of Health’s first team of experts arrived in Guangzhou on 20th January 2003. A report on the disease was sent to the Health Bureau on 27th January 2003 (see Huang 2004).

According to the implemented regulations on the State Secrets Law concerning the handling of public health-related information in China in 2002, “any occurrence of infectious diseases should be classified as a state secret before they are announced by the Ministry of Health or organs authorised by the Ministry” (see Huang 2004). As the report was signalled as “top secret,” only top provincial health officials could open it (see Wallis 2005 and Whittaker et al., 2018). However, no authorised officials were available to open the document for a further three days.

After the document was finally read, a bulletin was distributed to hospitals across the province. However, the bulletin triggered few alerts as many health workers were on vacation due to Chinese New Year celebrations (see Pomfret 2003). Consequently, the wider public remained uninformed about the disease. It was not until 11th February 2003 that health officials held a public press conference to break the silence regarding the disease (see Hui and Ng 2007). Under IHR at the time, countries only had an obligation to report health threats listed by the WHO (see Gostin and Katz 2016). As SARS was a new virus, it was not listed under the IHR, and consequently, little information was shared with the WHO until early April 2003.

Hence, even though the virus was identified early in December 2002, little action was taken until April 2003, months after the epidemic had broken out. It was not the lack of detection that was responsible for a delay in response, but bureaucratic issues, lack of transparency, and lack of accountability mechanisms.

This is commonly seen in other hazards, such as the volcanic eruption of Mount Peele in 1902 where elections had delayed the evacuation and over 29,000 people were killed (see Chrétien and Brousse 1989), and Hurricane Katrina in 2007 where 1,833 people were killed, making this one of the costliest disasters in the United States due to a lack of bureaucratic coherence across different states (see Sylves 2006 and Abbott 2007).

Ebola, 2014: the gap caused by economic disincentives, lack of trust, and political pressure

China is not alone in delaying information about health crises. Indeed, there is a historical record of countries concealing and downplaying disease-related events. During the Ebola outbreak in 2014, the three countries most affected by the epidemic (Guinea, Sierra Leone and Liberia), consistently downplayed the extent of the disease.

Rumours began circulating in March 2014 of large numbers of deaths occurring in Monrovia that were suspected of being related to the Ebola Virus. However, the government only reported to one suspected case in the entire county of Montserrado (see Kamradt-Scott 2016 and WHO 2014).

Further, the Guinean Ministry for Health guide declared at the 67th World Health Assembly that the country was achieving tremendous progress in containing the outbreak, with five out of the six foci areas of the epidemics under control. The attempt at obfuscation persisted to the extent that when Liberia’s president finally asked for international assistance, it was highly criticised by both Guinea and Sierra Leone (see Kamradt-Scott 2016).

As stated by Lencucha and Bandara (2021), “Non-compliance may in some cases be a rational response to real and perceived risks rather than a lack of technical competence or political commitment”. In fact, the 2015 Survey of International Health Regulations National Focal Points found that 40% of state parties were concerned about the potential damage that notification of a possible PHEIC might inflict on their public image, and 33% were concerned by the damage it could have for tourism or trade (33%) (see Packer et al., 2021). States parties were also concerned about the confidentiality of reports to the WHO (45%) (see Packer et al., 2021).

Countries can suffer economic consequences resulting from trade restrictions and withdrawals of investment in local industries when reporting a health emergency. They may also face external pressure to downplay epidemics from neighbouring countries relying heavily on tourism.

Covid-19, 2019: the gap reinforced by ineffective risk communication, and lack of international coordination 

The WHO received the first alert to Covid-19 from China on 31st December 2019. By 5th January 2020, the WHO had already done a preliminary evaluation and released its first report on the Covid-19 epidemic. On the 10th January 2020, the first set of guidelines to help countries detect, track and respond to potential cases were published.

The WHO Director-General convened the first emergency meeting under the IHR on 23rd January 2020 to determine if the Covid-19 outbreak was a PHEIC. However, it did not reach a consensus, and a PHEIC was not declared. At that time, 557 cases had been reported, and four countries confirmed exported (travel-related) cases from China (IHR 2020).

Finally, on the 30th January 2020, seven days after its first emergency meeting, and one month since it received its first alert of Covid-19 from China, the WHO emergency meeting reconvened and declared a public health emergency of international concern. By then, 7,711 cases were confirmed in China alone and an additional 83 reported cases in eighteen other countries (see WHO 2020).

The WHO took one month to conduct its initial risk assessment for Covid-19 and issue its official warning, releasing its first strategic response plan for countries internationally a few days later, on 4th February 2020. However, even once a PHEIC was declared, most countries outside Asia still ignored the warning for up to six weeks (see Singh et al., 2021).

The official global warning system for diseases of international concern failed to result in efficient and rapid responses. However, the warning failed not because of the lack of early detection, but a failure to translate the alert into effective risk communication and coordinated action among countries internationally.

Similarly, the loss of credibility in the United Kingdom’s Covid-19 alert level systems was not the result of a lack of detection but was due to inconsistency in how risk was communicated, and a failure to translate the information into clear and useful public guidance measures (see Fearnley and Dixon 2020).

Lastly, Garcia and Fearnley (2021) highlighted that warning systems for natural hazards often do not work, not because of the science or technology underpinning them, but because of social and institutional factors impacting their effectiveness and rapidity of the response.

Key insights

While surveillance mechanisms, early detection and science are essential components of any effective warning system for health threats, they do not necessarily result in better or earlier responses. Health warning systems need to be understood and function within the economic, political and social contexts in which they are deployed, because those are key factors that influence both the transmission of, and response to, health threats beyond the physical and chemical properties of the pathogen. Social science analyses are crucial in this regard and need to be used as follows:

• To evaluate and address the governmental, political or/and social barriers that may hinder information from being communicated to the broader public and delay responses (see Hale et al., 2021 and Tang et al., 2022).
• To assess which methods, languages and platforms are more effective to communicate risk and uncertainty depending on the population and to ensure warning systems are inclusive (see Red Cross, Disability Alliance and Inter-Agency Standing Committee resources).
• To build trust with countries to ensure data sharing (see Lencucha and Bandara 2021).
• To determine which accountability and incentives mechanisms can be put in place nationally and internationally to promote early and cohesive action (see Faviero et al., 2022 and Worsnop 2019).
• To ensure risk communication is integrated with coordination networks and action mechanisms (both internationally and nationally), with both pre-established and flexible mechanisms to facilitate the implementation of an action plan (see Burton et al., 2012).