Care and Treatment to Reduce the Severity of Pandemic Illness
During a pandemic, health authorities work to reduce the severity of illness through patient care and treatment, which can help decrease the likelihood of severe outcomes such as hospitalizations and deaths. Treatments may range from nonspecific, supportive care to disease-specific drugs. During the prepandemic period, plans to implement these measures should be developed and tested through simulation exercises.
Maintaining supportive care during an epidemic or pandemic can improve mortality rates by alleviating the symptoms of disease. During the 2014 West Africa Ebola epidemic, for example, evidence suggests that earlier case identification, supportive care, and rehydration therapy modestly reduced mortality (Walker and Whitty 2015). Indeed, despite the unavailability of antivirals or vaccines, efforts to engage communities with added medical supplies and trained clinicians decreased the case-fatality ratio moderately as more patients trusted, sought, and received clinical care (Aylward and others 2014). Medical supplies that may be needed for supportive care during a pandemic include hospital beds, disinfectants, ICU supplies (such as ventilators), and personal protective equipment (WHO 2015b).
Medical interventions for pandemic influenza include antiviral drugs and antibiotics to treat bacterial coinfections. Antivirals especially may reduce mortality when given within 48 hours of symptom onset (Domínguez-Cherit and others 2009; Jain and others 2009). However, because of delays in case identification and antiviral deployment (as discussed in box 17.2), LMICs may experience only limited benefits from antiviral drugs.
Potential for Scaling Up
The term scaling up refers to the expansion of health intervention coverage (Mangham and Hanson 2010). In the context of pandemic preparedness, successfully scaling up requires health systems to expand services to accommodate rapid increases in the number of suspected cases. Scaling up is facilitated by surge capacity (the ability to draw on additional clinical personnel, logisticians, and financial and other resources) as well as preexisting operational relationships and plans linking government, nongovernmental organizations, and the private sector. Ultimately, scaling up consists of having both local surge capacity and the absorptive capacity to accept outside assistance.
Local capacity building is vital, and some capacities may have particularly important positive externalities during outbreaks. During the 2014 Ebola importation into Nigeria, surge capacity that existed because of polio eradication efforts contributed to a more successful outbreak response (Yehualashet and others 2016). Key elements included national experience running an emergency operations center and the use of global positioning systems to support contact tracing (Shuaib and others 2014; WHO 2015a).
Stockpiling of vaccines, medicines (including antibiotics and antivirals), and equipment (such as masks, gowns, and ventilators) also can be useful for building local surge capacity (Dimitrov and others 2011; Jennings and others 2008; Morens, Taubenberger, and Fauci 2008; Radonovich and others 2009). During a pandemic, health systems can tap into stockpiles more quickly than they can procure supplies from external sources or boost production. However, there are five important considerations for keeping stockpiles:
Building a stockpile requires significant up-front costs, which can be especially prohibitive for LICs (Oshitani, Kamigaki, and Suzuki 2008).
Prepandemic vaccines may not be closely matched to the pathogen causing the pandemic.
The optimal size of a stockpile can be challenging to determine.
Stockpiles need to be refreshed regularly, because pharmaceuticals and equipment can reach expiration dates.
Robust health systems and channels for disseminating and using the stockpiles also must exist.
Boosting local production capacity for necessary supplies may be a viable strategy for pandemic preparedness and may circumvent some of the challenges associated with amassing stockpiles.
The 2009 influenza pandemic demonstrated how scaling up can affect the success rate of a mass vaccination campaign (table 17.5). Vaccination rates increased according to country income level, suggesting that vaccination campaigns were most successful in HICs, likely because of the size of their stockpiles, increased manufacturing capacity for vaccines, increased availability of vaccines, and more streamlined logistics in vaccine deployment.
Building local capacity to scale up is challenging, especially in LMICs. The biggest challenges include infrastructural gaps (such as weak road, transportation, and communications networks) and shortfalls in human resources (such as logisticians, epidemiologists, and clinical staff). Bilateral and multilateral aid organizations have channeled substantial funding into building and sustaining local technical capacities in LMICs. This type of investment is critically important. But, particularly in LMICs with weak health system capacity, progress in expanding local surge capacity likely will be slow.
Another key component of scaling up, especially in LMICs, is the ability to use external assistance effectively. During the 2014 West Africa Ebola epidemic, a surge of foreign clinicians, mobile medical units, and epidemiologists and other public health personnel was required to bolster limited local resources. LMICs can improve systems to facilitate and coordinate surges of foreign support in the following ways:
Streamline customs processes for critical medical supplies and drugs.
Establish mechanisms to coordinate the deployment and operations of foreign medical teams.
Build mechanisms to coordinate between military and humanitarian units involved in crisis response.
Even so, local absorptive capacity (that is, the ability to channel and use foreign assistance effectively) has its limits. Constraints in bureaucratic capacity, financial controls, logistics, and infrastructure all are likely to be most severe in the countries that most need foreign assistance to manage infectious disease crises.
Furthermore, although external assistance is a viable strategy during localized epidemics, it has limitations that are likely to arise during large-scale pandemics. First, supply constraints exist, including limits to the number of medical personnel (especially those with crisis response and infectious disease competencies) and the number of specialized resources (such as integrated mobile medical clinics available for deployment).
Second, during a severe pandemic, countries are likely to use such resources locally before providing medical assistance abroad. The global humanitarian system provides a critical reservoir of crisis response capacity and shock absorption. However, the humanitarian system currently is straining under the pressure of other crises, including upsurges in violent conflict (Stoddard and others 2015). A severe epidemic or pandemic can quickly outstrip international resources. Médecins Sans Frontières (Doctors Without Borders), an international health organization with deep experience providing Ebola treatment, found itself “pushed to the limits and beyond” during the 2014 West Africa Ebola epidemic (MSF 2015).
Risk Transfer Mechanisms
As with any other type of natural disaster, the risk from pandemics cannot be eliminated. Despite prevention efforts, pandemics will continue to occur and will at times overwhelm the systems that have been put in place to mitigate their health, societal, and economic effects. The residual risk may be significant, particularly for LMICs that lack the resilience or resources to absorb shocks to public health and public finances. Risk transfer mechanisms (such as specialized insurance facilities) offer an additional tool to manage this risk.
Risk-based insurance products are increasingly deployed in LMICs to pay for remediation and reconstruction costs following natural catastrophes such as hurricanes, floods, and droughts (ARC 2016; IFRC 2016). Insurance products for epidemics and pandemics require specific characteristics. First, insurance policies should be designed to release discretionary funds early in the course of an outbreak. In situations where financing poses a constraint to mobilizing personnel, drugs, or other supplies, payouts can be used to mobilize a public health response and mitigate further spread of disease, reducing the potential health and economic impacts of the pandemic. Second, because pandemics do not stay contained in national borders, a strong case can be made for mobilizing bilateral and multilateral financing of LMICs’ insurance premiums as a cost-effective way to improve global preparedness and support mitigation efforts. Third, risk transfer systems require the availability of rigorously and transparently compiled data to trigger a payout. In the context of pandemic insurance, the development of risk transfer systems requires countries to build the following capacities, among others:
Robust surveillance data to identify when an outbreak has reached sufficient scale to require the release of funds
Laboratory capacity to confirm the causative agent
Predefined contingency and response plans to spend the funds effectively upon their release.
Insurance facilities can create positive incentives for LMICs to invest in planning and capacity building. Insurance mechanisms may have other positive externalities: most notably, the potential release of funds may provide a strong incentive for the timely reporting of surveillance data. However, insurance facilities also may introduce perverse incentives (including incentives to distort surveillance data) and potential moral hazards (such as permitting riskier activities). These incentive problems may be mitigated in the design of the risk transfer mechanism, such as by providing coverage only when minimum requirements for surveillance accuracy are met, by having preset phased triggers for payouts, and by including incentive payouts for successfully containing an outbreak.
Relative to investments in basic health provision, building capacity in infectious disease surveillance systems and other dimensions of pandemic preparedness has uncertain and potentially distant benefits. In LICs where near-term health needs are acute, this can complicate the political and economic logic for investing in pandemic preparedness (Buckley and Pittluck 2016). The use of catastrophe modeling tools (such as EP curves) can clarify the benefit-cost rationale and the relevant time horizon for investments in preparedness, and it can inform the design and financial structure of pandemic insurance policies.
Figure 17.3 shows a country’s hypothetical pandemic preparedness budget allocation and the portion of risk transfer in estimated total costs of spread response. In this example, a country has a total budget of US$100 million to cover all aspects of pandemic preparedness during the prepandemic, spark, and spread periods. After allocating half of the funds for prepandemic and spark response activities, US$50 million is left for pandemic spread response. On the basis of its risk tolerance, the country makes a decision to manage its risk at the 3 percent annual probability point on its EP curve. Modeling estimates indicate that a successful response to a pandemic at this level would require at least US$125 million, which would fund spread response activities, shown in box 17.1. Because only US$50 million is left after allocation to prepandemic and spark response activities, this would leave a shortfall of US$75 million. Some or all of this shortfall could be offloaded to another entity, such as a catastrophe risk insurance pool, which would give the country access to a payout during a pandemic.