Capacity of Thailand to contain an emerging influenza pandemic

Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review

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Mathematical model capabilities to explore complex systems now enable priority-setting to consider local resource constraints.

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Common objectives of model-based analyses incorporating constraints are to assess real-world feasibility or allocate resources efficiently.

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Constraints may be incorporated via (i) model-based estimation; (ii) linkage of mathematical and health system models; or (iii) optimisation.

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Models can then project constrained intervention effects and costs and resource requirement s for delivering interventions at full scale.

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'Health system constraints' should be systematically defined for routine operationalisation in model-based priority-setting.

Priority setting for infectious disease control is increasingly concerned with physical input constraints and other real-world restrictions on implementation and on the decision process. These health system constraints determine the ‘feasibility’ of interventions and hence impact. However, considering them within mathematical models places additional demands on model structure and relies on data availability. This review aims to provide an overview of published methods for considering constraints in mathematical models of infectious disease.

We systematically searched the literature to identify studies employing dynamic transmission models to assess interventions in any infectious disease and geographical area that included non-financial constraints to implementation. Information was extracted on the types of constraints considered and how these were identified and characterised, as well as on the model structures and techniques for incorporating the constraints.

A total of 36 studies were retained for analysis. While most dynamic transmission models identified were deterministic compartmental models, stochastic models and agent-based simulations were also successfully used for assessing the effects of non-financial constraints on priority setting. Studies aimed to assess reductions in intervention coverage (and programme costs) as a result of constraints preventing successful roll-out and scale-up, and/or to calculate costs and resources needed to relax these constraints and achieve desired coverage levels. We identified three approaches for incorporating constraints within the analyses: (i) estimation within the disease transmission model; (ii) linking disease transmission and health system models; (iii) optimising under constraints (other than the budget).

The review highlighted the viability of expanding model-based priority setting to consider health system constraints. We show strengths and limitations in current approaches to identify and quantify locally-relevant constraints, ranging from simple assumptions to structured elicitation and operational models. Overall, there is a clear need for transparency in the way feasibility is defined as a decision criteria for its systematic operationalisation within models.

Case-Control Study of Use of Personal Protective Measures and Risk for SARS-CoV 2 Infection, Thailand

We evaluated effectiveness of personal protective measures against severe acute respiratory disease coronavirus 2 (SARS-CoV-2) infection. Our case-control study included 211 cases of coronavirus disease (COVID-19) and 839 controls in Thailand. Cases were defined as asymptomatic contacts of COVID-19 patients who later tested positive for SARS-CoV-2; controls were asymptomatic contacts who never tested positive. Wearing masks all the time during contact was independently associated with lower risk for SARS-CoV-2 infection compared with not wearing masks; wearing a mask sometimes during contact did not lower infection risk. We found the type of mask worn was not independently associated with infection and that contacts who always wore masks were more likely to practice social distancing. Maintaining >1 m distance from a person with COVID-19, having close contact for <15 minutes, and frequent handwashing were independently associated with lower risk for infection. Our findings support consistent wearing of masks, handwashing, and social distancing to protect against COVID-19.

Potential demand for respirators and surgical masks during a hypothetical influenza pandemic in the United States

Background. To inform planning for an influenza pandemic, we estimated US demand for N95 filtering facepiece respirators (respirators) by healthcare and emergency services personnel and need for surgical masks by pandemic patients seeking care.

Methods. We used a spreadsheet-based model to estimate demand for 3 scenarios of respirator use: base case (usage approximately follows epidemic curve), intermediate demand (usage rises to epidemic peak and then remains constant), and maximum demand (all healthcare workers use respirators from pandemic onset). We assumed that in the base case scenario, up to 16 respirators would be required per day per intensive care unit patient and 8 per day per general ward patient. Outpatient healthcare workers and emergency services personnel would require 4 respirators per day. Patients would require 1.2 surgical masks per day.

Results and Conclusions. Assuming that 20% to 30% of the population would become ill, 1.7 to 3.5 billion respirators would be needed in the base case scenario, 2.6 to 4.3 billion in the intermediate demand scenario, and up to 7.3 billion in the maximum demand scenario (for all scenarios, between 0.1 and 0.4 billion surgical masks would be required for patients). For pandemics with a lower attack rate and fewer cases (eg, 2009-like pandemic), the number of respirators needed would be higher because the pandemic would have longer duration. Providing these numbers of respirators and surgical masks represents a logistic challenge for US public health agencies. Public health officials must urgently consider alternative use strategies for respirators and surgical masks during a pandemic that may vary from current practices.

Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator

BACKGROUND

Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics.

RESULTS

The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources.

CONCLUSIONS

The AsiaFluCap Simulator is freely available software (http://www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software.

Health system resource gaps and associated mortality from pandemic influenza across six Asian territories

Background

Southeast Asia has been the focus of considerable investment in pandemic influenza preparedness. Given the wide variation in socio-economic conditions, health system capacity across the region is likely to impact to varying degrees on pandemic mitigation operations. We aimed to estimate and compare the resource gaps, and potential mortalities associated with those gaps, for responding to pandemic influenza within and between six territories in Asia.

Methods and Findings

We collected health system resource data from Cambodia, Indonesia (Jakarta and Bali), Lao PDR, Taiwan, Thailand and Vietnam. We applied a mathematical transmission model to simulate a “mild-to-moderate” pandemic influenza scenario to estimate resource needs, gaps, and attributable mortalities at province level within each territory. The results show that wide variations exist in resource capacities between and within the six territories, with substantial mortalities predicted as a result of resource gaps (referred to here as “avoidable” mortalities), particularly in poorer areas. Severe nationwide shortages of mechanical ventilators were estimated to be a major cause of avoidable mortalities in all territories except Taiwan. Other resources (oseltamivir, hospital beds and human resources) are inequitably distributed within countries. Estimates of resource gaps and avoidable mortalities were highly sensitive to model parameters defining the transmissibility and clinical severity of the pandemic scenario. However, geographic patterns observed within and across territories remained similar for the range of parameter values explored.

Conclusions

The findings have important implications for where (both geographically and in terms of which resource types) investment is most needed, and the potential impact of resource mobilization for mitigating the disease burden of an influenza pandemic. Effective mobilization of resources across administrative boundaries could go some way towards minimizing avoidable deaths.

Organizational Collaborative Capacity in Fighting Pandemic Crises

Collaborative capacity serves for organizations as the capacity to collaborate with other network players. Organizational capacity matters as collaboration outcomes usually go beyond single-shot implementation efforts or a single-minded focus on either the vertical dimension of program or the horizontal component. This review article explores organizational collaborative capacities from the perspective of public management, in particular, network theory. By applying the 5 attributes of network theory—interdependence, membership, resources, information, and learning—to the explanation of collaborative capacity in fighting pandemic crises, I argue in some ways organizational collaborative capacity is very much like an organization in its own right. Studying collaborative capacity in the battle against pandemics facilitate our understanding of multisectoral collaboration in technical, political, and institutional dimensions, and greatly advances the richness of capacity vocabulary in pandemic response and preparedness.

Pandemic influenza and health system resource gaps in Bali: an analysis through a resource transmission dynamics model

The failure to contain pandemic influenza A(H1N1) 2009 in Mexico has shifted global attention from containment to mitigation. Limited surveillance and reporting have, however, prevented detailed assessment of mitigation during the pandemic, particularly in low- and middle-income countries. To assess pandemic influenza case management capabilities in a resource-limited setting, the authors used a health system questionnaire and density-dependent, deterministic transmission model for Bali, Indonesia, determining resource gaps. The majority of health resources were focused in and around the provincial capital, Denpasar; however, gaps are found in every district for nursing staff, surgical masks, and N95 masks. A relatively low pathogenicity pandemic influenza virus would see an overall surplus for physicians, antivirals, and antimicrobials; however, a more pathogenic virus would lead to gaps in every resource except antimicrobials. Resources could be allocated more evenly across Bali. These, however, are in short supply universally and therefore redistribution would not fill resource gaps.

Pandemic preparedness in Asia: a role for law and ethics?

Management of pandemic influenza relies on complex coordination of many different dimensions of the health and social care systems, emergency services, levels of national and local government, civil society, communications and media, and cultural expectations. Law is one small but important component of those arrangements, which touch on fundamental ethical debates. This review demonstrates that the Asian region is actively engaging those issues in diverse ways in light of their varied socioeconomic and cultural backgrounds, but scope remains for prioritising further research into these relationships.

Emerging infectious diseases in southeast Asia: regional challenges to control

Southeast Asia is a hotspot for emerging infectious diseases, including those with pandemic potential. Emerging infectious diseases have exacted heavy public health and economic tolls. Severe acute respiratory syndrome rapidly decimated the region's tourist industry. Influenza A H5N1 has had a profound effect on the poultry industry. The reasons why southeast Asia is at risk from emerging infectious diseases are complex. The region is home to dynamic systems in which biological, social, ecological, and technological processes interconnect in ways that enable microbes to exploit new ecological niches. These processes include population growth and movement, urbanisation, changes in food production, agriculture and land use, water and sanitation, and the effect of health systems through generation of drug resistance. Southeast Asia is home to about 600 million people residing in countries as diverse as Singapore, a city state with a gross domestic product (GDP) of US$37,500 per head, and Laos, until recently an overwhelmingly rural economy, with a GDP of US$890 per head. The regional challenges in control of emerging infectious diseases are formidable and range from influencing the factors that drive disease emergence, to making surveillance systems fit for purpose, and ensuring that regional governance mechanisms work effectively to improve control interventions.

Preparedness against an influenza pandemic of the frontline health facilities in southern Thailand: factor and cluster analyses

Preparedness at the frontline health level is essential for early detection, response, and prevention of the spread of an influenza pandemic in a community. This study aimed to assess and document patterns of basic preparedness for a threat of an influenza pandemic of the frontline health facilities in southern Thailand. A cross-sectional assessment was conducted among health centers. Key staffs were asked to complete a checklist consisting of facility access plan, surveillance, infection control, risk communication and health information dissemination, and health alert network and information technology.

RESULTS

showed that the frontline health facilities were not well prepared for the threat in the early stages of a pandemic. Using cluster analysis, 6 variation patterns of preparedness were identified, with infection control being the weakest. Grassroots healthcare should be encouraged and supported to increase capacities in preparedness against influenza pandemics. Periodical monitoring by higher levels is needed.

Health service resource needs for pandemic influenza in developing countries: a linked transmission dynamics, interventions and resource demand model

We used a mathematical model to describe a regional outbreak and extrapolate the underlying health-service resource needs. This model was designed to (i) estimate resource gaps and quantities of resources needed, (ii) show the effect of resource gaps, and (iii) highlight which particular resources should be improved. We ran the model, parameterized with data from the 2009 H1N1v pandemic, for two provinces in Thailand. The predicted number of preventable deaths due to resource shortcomings and the actual resource needs are presented for two provinces and for Thailand as a whole. The model highlights the potentially huge impact of health-system resource availability and of resource gaps on health outcomes during a pandemic and provides a means to indicate where efforts should be concentrated to effectively improve pandemic response programmes.

Patterns of perception toward influenza pandemic among the front-line responsible health personnel in southern Thailand: a Q methodology approach

Background

Thailand has joined the World Health Organization effort to prepare against a threat of an influenza pandemic. Regular monitoring on preparedness of health facilities and assessment on perception of the front-line responsible health personnel has never been done. This study aimed to document the patterns of perception of health personnel toward the threat of an influenza pandemic.

Methods

Q methodology was applied to a set of 385 health personnel in charge of influenza pandemic preparedness in the three southernmost provinces of Thailand. Subjects were asked to rank 33 statements about various issues of influenza pandemic according to a pre-designed score sheet having a quasi-normal distribution on a continuous 9-point bipolar scale ranging from -4 for strongly disagree to +4 for strongly agree. The Q factor analysis method was employed to identify patterns based on the similarity and dissimilarity among health personnel.

Results

There were three main patterns of perception toward influenza pandemic with moderate correlation coefficients between patterns ranging from 0.37 to 0.55. Pattern I, health personnel, which we labeled pessimistic, perceived themselves as having a low self-efficacy. Pattern II, which we labeled optimistic, perceived the threat to be low severity and low vulnerability. Pattern III, which we labeled mixed, perceived low self-efficacy but low vulnerability. Across the three patterns, almost all the subjects had a high expectancy that execution of recommended measures can mitigate impacts of the threat of an influenza pandemic, particularly on multi-measures with high factor scores of 4 in all patterns. The most conflicting area was vulnerability on the possible impacts of an influenza pandemic, having factor scores of high (3), low (-4), and neutral (0) for patterns I, II, and III, respectively.

Conclusion

Strong consistent perceptions of response efficacy against an influenza pandemic may suggest a low priority to convince health personnel on the efficacy of the recommended measures. Lack of self-efficacy in certain sub-groups indicates the need for program managers to improve self-confidence of health personnel to participate in an emergency response.