Control of neglected tropical diseases (NTDs) via mass drug administration (MDA) has increased considerably over the past decade, but strategies focused exclusively on human treatment show limited efficacy. This paper investigated trade-offs between drug and environmental treatments in the fight against NTDs by using schistosomiasis as a case study. We use optimal control techniques where the planner’s objective is to treat the disease over a time horizon at the lowest possible total cost, where the total costs include treatment, transportation and damages (reduction in human health). We show that combining environmental treatments and drug treatments reduces the dependency on MDAs and that this reduction increases when the planners take a longer-run perspective on the fight to reduce NTDs. Our results suggest that NTDs with environmental reservoirs require moving away from a reliance solely on MDA to integrated treatment involving investment in both drug and environmental controls.
The COVID-19 Vaccines Global Access (COVAX) is a World Health Organization (WHO) initiative that aims for an equitable access of COVID-19 vaccines. Despite potential heterogeneous infection levels across a country, countries receiving allotments of vaccines may follow WHO’s allocation guidelines and distribute vaccines based on a jurisdictions’ relative population size. Utilizing economic—epidemiological modeling, we benchmark the performance of this pro rata allocation rule by comparing it to an optimal one that minimizes the economic damages and expenditures over time, including a penalty representing the social costs of deviating from the pro rata strategy. The pro rata rule performs better when the duration of naturally- and vaccine-acquired immunity is short, when there is population mixing, when the supply of vaccine is high, and when there is minimal heterogeneity in demographics. Despite behavioral and epidemiological uncertainty diminishing the performance of the optimal allocation, it generally outperforms the pro rata vaccine distribution rule.
Although the COVID-19 disease burden is heterogeneous across space, the U.S. National Academies of Sciences, Engineering, and Medicine recommends an equitable spatial allocation of pharmaceutical interventions based, for example, on population size, in the interest of speed and workability. Utilizing economic–epidemiological modeling, we benchmark the performance of ad hoc allocation rules of scarce vaccines and drugs by comparing them to the rules for a vaccine and for a drug treatment that minimize the economic damages and expenditures over time, including a penalty cost representing the social costs of deviating from an ad hoc allocation. Under different levels of vaccine and drug scarcity, we consider scenarios where length of immunity and compliance to travel restrictions vary, and consider the robustness of the rules when assumptions regarding these factors are incorrect. Because drugs and vaccines attack different points in the disease pathology, the benefits from deviating from the ad hoc rule differ. For drug treatment, optimal policies often allocate all available treatments to one jurisdiction for a period of time, while ad hoc rules act to spread out treatments across jurisdictions. For vaccines, the benefits from deviating are especially high when immunity is permanent, when there is compliance to travel restrictions, and when the supply of vaccine is low. Interestingly, a lack of compliance to travel restrictions pushes the optimal allocations of vaccine towards the ad hoc and improves the relative robustness of the ad hoc rules, as the mixing of the populations reduces the spatial heterogeneity in disease burden.Antiviral DrugsSpatial Prioritization: Drugs should be directed towards the region that has fewer infections; optimal allocation gives rise to extreme allocations where it is preferable to give all of the allotment to one jurisdiction for a period of time rather than an allocation based on relative levels of infected individuals.Epidemiological Consequences of Spatial Prioritization: Compared to the ad hoc allocation rule, where more treatments go to locations with more infected individuals, the optimal allocation results in a higher number of cumulative cases in the jurisdictions that have a higher initial level of infected individuals and fewer cumulative cases in the jurisdictions that have a lower initial level of infected individuals. Over the period of four months, however, how well the optimal more extreme allocation does in aggregate (across jurisdictions) relative to an aggregate ad hoc allocation is dependent on epidemiological, behavioral, and logistical factors.Robustness of Spatial Allocation: The optimal allocations are not robust to incomplete information on compliance to travel restrictions and immunity, and perform worse than the ad hoc allocations in cases where they are designed under one set of assumptions but yet the true state of the world is different.Policy Recommendation: Until we have more information about compliance and immunity, our analysis leads us to conclude that ad hoc allocations may be the least risky option for the allocation of antiviral drugs.VaccinesSpatial Prioritization: Compared to an ad hoc allocation rule based on relative population size as recommended by the US National Academies of Science, Engineering, and Medicine, the optimal allocation of vaccine favors the least-burdened jurisdiction, resulting in an unequal distribution from a resource allocation perspective.Epidemiological Consequences of Spatial Prioritization: The optimal allocation results in a more equal level of infection across jurisdictions in each period while the ad hoc allocation results in a more equal distribution of aggregate cumulative infections.Robustness of Spatial Allocation: In terms of economic expenditures and cumulative cases, the optimal allocation is less impacted when assumptions on immunity are incorrect than when wrong about compliance to travel restrictions.Policy Recommendation: Imposing strict travel restrictions, or e.g. forcing quarantine when traveling to another jurisdiction, and prioritizing vaccination in jurisdictions that have lower initial disease burden could prevent a significant number of cases.
Nous analysons l’exploration et l’extraction d’une ressource naturelle non renouvelable dans un contexte d’asymétrie d’information. Le principal délègue l’exploitation d’une ressource à un agent (une firme) qui possède de l’information privée concernant ses coûts d’exploration; cette firme possédera également de l’information privée concernant ses coûts d’extraction une fois que le stock de réserves sera mis au jour et viendra contraindre l’extraction. Le principal peut seulement s’engager pour la période courante : un menu de contrat subventions-découvertes pour la période d’exploration, un menu de contrat redevances-extraction conditionnel au montant de réserves mis au jour pour la période d’extraction. Comparé avec la situation de premier rang où l’information est symétrique, le contrat optimal en extraction entraîne une hausse des découvertes des réserves mises au jour pour la firme la plus efficace et possiblement d’autres firmes, alors que le contrat optimal en exploration entraîne une réduction du montant mis au jour, particulièrement pour les firmes les moins efficaces en exploration. Nous détaillons les implications de l’asymétrie d’information et les formes que prennent les inefficacités : réserves abandonnées, utilisation excessive de ressources à bas coûts et niveau de sophistication technologique inefficace dans les secteurs d’exploration et d’extraction.
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