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Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.
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COVID-19 , Doenças Negligenciadas , Medicina Tropical , Doenças Negligenciadas/prevenção & controle , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , Modelos Teóricos , Organização Mundial da Saúde , SARS-CoV-2 , Tomada de Decisões , Saúde GlobalRESUMO
Coronavirus disease 2019 (COVID-19) booster vaccination has been implemented globally in the midst of surges in infection due to the Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of the present study was to present a framework to estimate the proportion of the population that is immune to symptomatic SARS-CoV-2 infection with the Omicron variant (immune proportion) in Japan, considering the waning of immunity resulting from vaccination and naturally acquired infection. We quantified the decay rate of immunity against symptomatic infection with Omicron conferred by the second and third doses of COVID-19 vaccine. We estimated the current and future vaccination coverage for the second and third vaccine doses from February 17, 2021 to August 1, 2022 and used data on the confirmed COVID-19 incidence from February 17, 2021 to April 10, 2022. From this information, we estimated the age-specific immune proportion over the period from February 17, 2021 to August 1, 2022. Vaccine-induced immunity, conferred by the second vaccine dose in particular, was estimated to rapidly wane. There were substantial variations in the estimated immune proportion by age group because each age cohort experienced different vaccination rollout timing and speed as well as a different infection risk. Such variations collectively contributed to heterogeneous immune landscape trajectories over time and age. The resulting prediction of the proportion of the population that is immune to symptomatic SARS-CoV-2 infection could aid decision-making on when and for whom another round of booster vaccination should be considered. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
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COVID-19 , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , SARS-CoV-2 , Vacinas contra COVID-19 , Japão/epidemiologia , VacinaçãoRESUMO
COVID-19 vaccination commenced globally in December 2020. Japan launched its vaccination rollout on February 17, 2021 and commenced booster vaccination campaign on December 1, 2021. It has been crucial to grasp the immune landscape in the country in order to aid in decision-making and evaluation of vaccination campaigns as well as understating the transmission dynamics of various variants of SARS-CoV-2. The present article shows a framework that enables us to predict the immune landscape, specifically, the proportion of immune population, using a mathematical modeling approach. This involved: prediction of vaccine coverage; estimation of vaccine effectiveness against the dominant SARS-CoV-2 variant in circulation; the quantification of increasing vaccine effectiveness (immune-build up) since receiving the first dose; the estimation of waning rate of vaccine effectiveness since receiving the second and third doses; and the consideration on the infection-induced immunity.
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BACKGROUND: Trachoma is the commonest infectious cause of blindness worldwide. Efforts are being made to eliminate trachoma as a public health problem globally. However, as prevalence decreases, it becomes more challenging to precisely predict prevalence. We demonstrate how model-based geostatistics (MBG) can be used as a reliable, efficient, and widely applicable tool to assess the elimination status of trachoma. METHODS: We analysed trachoma surveillance data from Brazil, Malawi, and Niger. We developed geostatistical Binomial models to predict trachomatous inflammation-follicular (TF) and trachomatous trichiasis (TT) prevalence. We proposed a general framework to incorporate age and gender in the geostatistical models, whilst accounting for residual spatial and non-spatial variation in prevalence through the use of random effects. We also used predictive probabilities generated by the geostatistical models to quantify the likelihood of having achieved the elimination target in each evaluation unit (EU). RESULTS: TF and TT prevalence varied considerably by country, with Brazil showing the lowest prevalence and Niger the highest. Brazil and Malawi are highly likely to have met the elimination criteria for TF in each EU, but, for some EUs, there was high uncertainty in relation to the elimination of TT according to the model alone. In Niger, the predicted prevalence varied significantly across EUs, with the probability of having achieved the elimination target ranging from values close to 0% to 100%, for both TF and TT. CONCLUSIONS: We demonstrated the wide applicability of MBG for trachoma programmes, using data from different epidemiological settings. Unlike the standard trachoma prevalence survey approach, MBG provides a more statistically rigorous way of quantifying uncertainty around the achievement of elimination prevalence targets, through the use of spatial correlation. In addition to the analysis of existing survey data, MBG also provides an approach to identify areas in which more sampling effort is needed to improve EU classification. We advocate MBG as the new standard method for analysing trachoma survey outputs.
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Tracoma , Triquíase , Humanos , Lactente , Tracoma/epidemiologia , Tracoma/prevenção & controle , Estudos Transversais , Saúde Pública , Inquéritos e Questionários , Malaui/epidemiologia , Triquíase/epidemiologia , Triquíase/prevenção & controle , PrevalênciaRESUMO
OBJECTIVES: COVID-19 vaccination in Japan started on February 17, 2021. Because the timing of vaccination and the risk of severe COVID-19 greatly varied with age, the present study aimed to monitor the age-specific fractions of the population who were immune to SARS-CoV-2 infection after vaccination. METHODS: Natural infection remained extremely rare, accounting for less than 5% of the population by the end of 2021; thus, we ignored natural infection-induced immunity and focused on vaccine-induced immunity. We estimated the fraction of the population immune to infection by age group using vaccination registry data from February 17, 2021, to October 17, 2021. We accounted for two important sources of delay: (i) reporting delay and (ii) time from vaccination until immune protection develops. RESULTS: At the end of the observation period, the proportion of individuals still susceptible to SARS-CoV-2 infection substantially varied by age and was estimated to be ≥90% among people aged 0-14 years, in contrast to approximately 20% among the population aged ≥65 years. We also estimated the effective reproduction number over time using a next-generation matrix while accounting for differences in the proportion immune to infection by age. CONCLUSION: The COVID-19 immune landscape greatly varied by age, and a substantial proportion of young adults remained susceptible. Vaccination contributed to a marked decrease in the reproduction number.
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COVID-19 , COVID-19/epidemiologia , COVID-19/prevenção & controle , Vacinas contra COVID-19 , Suscetibilidade a Doenças , Humanos , Japão/epidemiologia , SARS-CoV-2 , Vacinação , Adulto JovemRESUMO
In Japan, a prioritized COVID-19 vaccination program using Pfizer/BioNTech messenger RNA (mRNA) vaccine among healthcare workers commenced on February 17, 2021. As vaccination coverage increases, clusters in healthcare and elderly care facilities including hospitals and nursing homes are expected to be reduced. The present study aimed to explicitly estimate the protective effect of vaccination in reducing cluster incidence in those facilities. A mathematical model was formulated using three pieces of information: (1) the incidence of clusters in facilities from October 26, 2020 to June 27, 2021; (2) the incidence of confirmed COVID-19 cases during the same period; and (3) vaccine doses among healthcare workers from February 17 to June 27, 2021, extracted from the national Vaccination System database. We found that the estimated proportion at risk in healthcare and elderly care facilities declined substantially as the vaccination coverage among healthcare workers increased; the greater risk reduction was observed in healthcare facilities, at 0.10 (95% confidence interval (CI): 0.04-0.16) times that in the pre-vaccination period, while that in elderly care facilities was 0.34 (95% CI: 0.24-0.43) times that in the earlier period. The averted numbers of clusters in healthcare facilities and elderly care facilities were estimated to be 247 (95% CI: 210-301) and 279 (95% CI: 218-354), respectively. Prioritized vaccination among healthcare workers had a marked impact on preventing the incidence of clusters in facilities.
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COVID-19 , Idoso , COVID-19/epidemiologia , COVID-19/prevenção & controle , Vacinas contra COVID-19/uso terapêutico , Atenção à Saúde , Pessoal de Saúde , Humanos , Japão/epidemiologia , SARS-CoV-2 , VacinaçãoRESUMO
Background: In Japan, vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was initiated on 17 February 2021, mainly using messenger RNA vaccines and prioritizing health care professionals. Whereas nationwide vaccination alleviated the coronavirus disease 2019 (COVID-19)-related burden, the population impact has yet to be quantified in Japan. We aimed to estimate the numbers of COVID-19 cases and deaths prevented that were attributable to the reduced risk among vaccinated individuals via a statistical modeling framework. Methods: We analyzed confirmed cases registered in the Health Center Real-time Information-sharing System on COVID-19 (3 March-30 November 2021) and publicly reported COVID-19-related deaths (24 March-30 November 2021). The vaccination coverage over this time course, classified by age and sex, was extracted from vaccine registration systems. The total numbers of prevented cases and deaths were calculated by multiplying the daily risk differences between unvaccinated and vaccinated individuals by the population size of vaccinated individuals. Findings: For both cases and deaths, the averted numbers were estimated to be the highest among individuals aged 65 years and older. In total, we estimated that 564,596 (95% confidence interval: 477,020-657,525) COVID-19 cases and 18,622 (95% confidence interval: 6522-33,762) deaths associated with SARS-CoV-2 infection were prevented owing to vaccination during the analysis period (i.e., fifth epidemic wave, caused mainly by the Delta variant). Female individuals were more likely to be protected from infection following vaccination than male individuals whereas more deaths were prevented in male than in female individuals. Interpretation: The vaccination program in Japan led to substantial reductions in the numbers of COVID-19 cases and deaths (33% and 67%, respectively). The preventive effect will be further amplified during future pandemic waves caused by variants with shared antigenicity. Funding: This project was supported by the Japan Science and Technology Agency; the Japan Agency for Medical Research and Development; the Japan Society for the Promotion of Science; and the Ministry of Health, Labour and Welfare.
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Background: Public health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility. Materials and Methods: We investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (R t ) before and after these interventions, and then analyzed the relationship between lower R t values and each PHSM. Results: With implementation of pre-emergency measures (PEM) in 16 prefectures, the R t was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated R t < 1, and the average relative reduction was 26%-39%. No single intervention was identified that uniquely resulted in an R t value < 1. Conclusion: An SoE can substantially reduce the R t and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the R t value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.