Modeling vaccination strategies with limited early COVID-19 vaccine access in low- and middle-income countries: A case study of Thailand

A novel comparison framework for epidemiological strategies applied to age-based restrictions versus horizontal lockdowns

During an epidemic, such as the COVID-19 pandemic, policy-makers are faced with the decision of implementing effective, yet socioeconomically costly intervention strategies, such as school and workplace closure, physical distancing, etc. In this study, we propose a rigorous definition of epidemiological strategies. In addition, we develop a scheme for comparing certain epidemiological strategies, with the goal of providing policy-makers with a tool for their systematic comparison. Then, we put the suggested scheme to the test by employing an age-based epidemiological compartment model introduced in Bitsouni et al. (2024), coupled with data from the literature, in order to compare the effectiveness of age-based and horizontal interventions. In general, our findings suggest that these two are comparable, mainly at a low or medium level of intensity.

Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models

As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.

Interorganizational systems without hierarchy: immunization information systems

PURPOSE

The 2020-2021 COVID-19 pandemic spurred change across multiple healthcare industries. This study explores how managing vaccination data in the United States of America required cooperation among many different organizations necessitated by an emergency response. We studied how individual states interacted with the federal government to address the need for vaccination-related information during the pandemic.

DESIGN/METHODOLOGY/APPROACH

In total, 11 interviews were conducted with individuals responsible for collecting vaccination data and reporting it to the US Federal Government. Seven of those individuals were directors of USA jurisdictional Immunization Information Systems (IIS). Archival data were also combined with the interview responses to inform the analysis and development of guidelines.

FINDINGS

States across the USA had different ways of tracking and storing immunization data that was heavily influenced by state-level and federal legislation. The lack of a universal patient identifier made cross-state patient identification difficult. Federal requirements for reporting dictated much of how the different state-level entities collected, stored and reported data.

PRACTICAL IMPLICATIONS

This study highlights the importance of data interoperability and data sharing by exploring how a loosely coupled set of entities without direct top-down control or a profit motive can govern data effectively. Our analysis provides greater clarity about the interactions between different stakeholders in a complex system.

ORIGINALITY/VALUE

This study presents primary interviews of 11 individuals, each responsible for tracking and reporting immunization information. Analysis of the data expands existing research on IIS on data sharing, system interoperability and dynamic pandemic responses.

AH, Storer RJ, Ounjai P, Kanthawee P, Ngamwongsatit N, Kupwiwat R, Kupwiwat C, Brimson JM, Devanga Ragupathi NK, Charuluxananan S, Leelahavanichkul A, Kanjanabuch T, Higgins PG, Badavath VN, Amarasiri M, Verhasselt V, Kicic A, Chatsuwan T, Pirzada K, Jalali F, Reiersen AM, Abe S, Ishikawa H. Early treatment with fluvoxamine, bromhexine, cyproheptadine, and niclosamide to prevent clinical deterioration in patients with symptomatic COVID-19: a randomized clinical trial

Background

Repurposed drugs with host-directed antiviral and immunomodulatory properties have shown promise in the treatment of COVID-19, but few trials have studied combinations of these agents. The aim of this trial was to assess the effectiveness of affordable, widely available, repurposed drugs used in combination for treatment of COVID-19, which may be particularly relevant to low-resource countries.

Methods

We conducted an open-label, randomized, outpatient, controlled trial in Thailand from October 1, 2021, to June 21, 2022, to assess whether early treatment within 48-h of symptoms onset with combinations of fluvoxamine, bromhexine, cyproheptadine, and niclosamide, given to adults with confirmed mild SARS-CoV-2 infection, can prevent 28-day clinical deterioration compared to standard care. Participants were randomly assigned to receive treatment with fluvoxamine alone, fluvoxamine + bromhexine, fluvoxamine + cyproheptadine, niclosamide + bromhexine, or standard care. The primary outcome measured was clinical deterioration within 9, 14, or 28 days using a 6-point ordinal scale. This trial is registered with ClinicalTrials.gov (NCT05087381).

Findings

Among 1900 recruited, a total of 995 participants completed the trial. No participants had clinical deterioration by day 9, 14, or 28 days among those treated with fluvoxamine plus bromhexine (0%), fluvoxamine plus cyproheptadine (0%), or niclosamide plus bromhexine (0%). Nine participants (5.6%) in the fluvoxamine arm had clinical deterioration by day 28, requiring low-flow oxygen. In contrast, most standard care arm participants had clinical deterioration by 9, 14, and 28 days. By day 9, 32.7% (110) of patients in the standard care arm had been hospitalized without requiring supplemental oxygen but needing ongoing medical care. By day 28, this percentage increased to 37.5% (21). Additionally, 20.8% (70) of patients in the standard care arm required low-flow oxygen by day 9, and 12.5% (16) needed non-invasive or mechanical ventilation by day 28. All treated groups significantly differed from the standard care group by days 9, 14, and 28 (p < 0.0001). Also, by day 28, the three 2-drug treatments were significantly better than the fluvoxamine arm (p < 0.0001). No deaths occurred in any study group. Compared to standard care, participants treated with the combination agents had significantly decreased viral loads as early as day 3 of treatment (p < 0.0001), decreased levels of serum cytokines interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and interleukin-1 beta (IL-1β) as early as day 5 of treatment, and interleukin-8 (IL-8) by day 7 of treatment (p < 0.0001) and lower incidence of post-acute sequelae of COVID-19 (PASC) symptoms (p < 0.0001). 23 serious adverse events occurred in the standard care arm, while only 1 serious adverse event was reported in the fluvoxamine arm, and zero serious adverse events occurred in the other arms.

Interpretation

Early treatment with these combinations among outpatients diagnosed with COVID-19 was associated with lower likelihood of clinical deterioration, and with significant and rapid reduction in the viral load and serum cytokines, and with lower burden of PASC symptoms. When started very soon after symptom onset, these repurposed drugs have high potential to prevent clinical deterioration and death in vaccinated and unvaccinated COVID-19 patients.

Funding

Ped Thai Su Phai (Thai Ducks Fighting Danger) social giver group.

Vaccination strategies impact the probability of outbreak extinction: A case study of COVID-19 transmission

Mass vaccination has proven to be an effective control measure for mitigating the transmission of infectious diseases. Throughout history, various vaccination strategies have been employed to control infections and terminate outbreaks. In this study, we utilized the transmission of COVID-19 as a case study and constructed a stochastic age-structured compartmental model to investigate the effectiveness of different vaccination strategies. Our analysis focused on estimating the outbreak extinction probability under different vaccination scenarios in both homogeneous and heterogeneous populations. Notably, we found that population heterogeneity can enhance the likelihood of outbreak extinction at varying levels of vaccine coverage. Prioritizing vaccinations for individuals with higher infection risk was found to maximize outbreak extinction probability and reduce overall infections, while allocating vaccines to those with higher mortality risk has been proven more effective in reducing deaths. Moreover, our study highlighted the significance of booster doses as the vaccine effectiveness wanes over time, showing that they can significantly enhance the extinction probability and mitigate disease transmission.

AH, Fernandez S, Huang AT, Vatanaprasan P, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Ngamwongsatit N, Badavath VN, Thuptimdang W, Leelahavanichkul A, Kanjanabuch T, Miyanaga K, Cui L, Nanbo A, Shibuya K, Kupwiwat R, Sano D, Furukawa T, Sei K, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, Ishikawa H, Amarasiri M, Modchang C, Wannigama DL. Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission

This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.