Non-linear associations between meteorological factors, ambient air pollutants and major mosquito-borne diseases in Thailand.

BACKGROUND: Transmission intensity for mosquito-borne diseases are highly heterogenous and multi-factorial. Understanding risk factors associated to disease transmission allow the optimization of vector control. This study sets out to understand and compare the combined anthropogenic and environmental risk factors of four major mosquito-borne diseases, dengue, malaria, chikungunya and Japanese encephalitis in Thailand. METHODS: An integrated analysis of mosquito-borne diseases, meteorological and ambient air pollutants of 76 provinces of Thailand was conducted over 2003-2021. We explored the use of generalized linear models and generalized additive models to consider both linear and non-linear associations between meteorological factors, ambient air pollutants and mosquito-borne disease incidence. Different assumptions on spatio-temporal dependence and nonlinearity were considered through province-specific and panel models, as well as different spline functions. Disease-specific model evidence was assessed to select best-fit models for epidemiological inference downstream. RESULTS: Analyses indicated several findings which can be generally applied to all diseases explored: (1) higher AH above mean values was positively associated with disease case counts (2) higher total precipitation above mean values was positively associated with disease case counts (3) extremely high temperatures were negatively associated with disease case counts (4) higher SO2 and PM2.5 surface concentrations were negatively associated with disease case counts. However, the relationships between disease and RH, non-extreme temperatures and CO surface concentration were more mixed, with directions of associations changing across the different diseases considered. CONCLUSIONS: This study found protective and enhancing effects of meteorological and ambient air pollutant factors on mosquito-borne diseases burdens in Thailand. Further studies should employ these factors to understand and predict risk factors associated with mosquito-borne disease transmission.

EpiMix: A novel method to estimate effective reproduction number.

Transmission potential of a pathogen, often quantified by the time-varying reproduction number Rt, provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for Rt estimation, wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework. Using Integrated Nested Laplace Approximation, EpiMix is able to efficiently generate reliable, deterministic Rt estimates. In the simulations and case studies performed, we further demonstrated the method's robustness in low-incidence scenarios, together with other merits, including its flexibility in selecting variables and tolerance of varying reporting rates. All these make EpiMix a potentially useful tool for real-time Rt estimation provided that the serial interval distribution, time series of case counts and external influencing factors are available.

Border Control for Infectious Respiratory Disease Pandemics: A Modelling Study for H1N1 and Four Strains of SARS-CoV-2.

Post-pandemic economic recovery relies on border control for safe cross-border movement. Following the COVID-19 pandemic, we investigate whether effective strategies generalize across diseases and variants. For four SARS-CoV-2 variants and influenza A-H1N1, we simulated 21 strategy families of varying test types and frequencies, quantifying expected transmission risk, relative to no control, by strategy family and quarantine length. We also determined minimum quarantine lengths to suppress relative risk below given thresholds. SARS-CoV-2 variants showed similar relative risk across strategy families and quarantine lengths, with at most 2 days' between-variant difference in minimum quarantine lengths. ART-based and PCR-based strategies showed comparable effectiveness, with regular testing strategies requiring at most 9 days. For influenza A-H1N1, ART-based strategies were ineffective. Daily ART testing reduced relative risk only 9% faster than without regular testing. PCR-based strategies were moderately effective, with daily PCR (0-day delay) testing requiring 16 days for the second-most stringent threshold. Viruses with high typical viral loads and low transmission risk given low viral loads, such as SARS-CoV-2, are effectively controlled with moderate-sensitivity tests (ARTs) and modest quarantine periods. Viruses with low typical viral loads and substantial transmission risk at low viral loads, such as influenza A-H1N1, require high-sensitivity tests (PCR) and longer quarantine periods.

The impact of earlier reopening to travel in the Western Pacific on SARS-CoV-2 transmission.

Background: The COVID-19 pandemic has led to a fall of over 70% in international travel, resulting in substantial economic damages. The impact is especially pronounced in the Asia-Pacific region, where governments have been slow to relax border restrictions. Methods: A retrospective approach was used to construct notional epidemic trajectories for eight Asia-Pacific countries or regions, from June to November 2021, under hypothetical scenarios of earlier resumption of international travel and selective border reopening. The numbers of local infections and deaths over the prediction window were calculated accordingly. Results: Had quarantine-free entry been permitted for all travellers from all the regions investigated, and travel volumes recovered to the 2019 levels, Australia, New Zealand, and Singapore would have been the three most severely affected regions, with at least doubled number of deaths, while infections would have increased marginally (< 5%) for Japan, Malaysia, and Thailand. Conclusions: Earlier resumption of travel in Asia-Pacific, while maintaining a controlled degree of importation risk, could have been implemented through selective border-reopening strategies and on-arrival testing. Once countries had experienced large, localized COVID-19 outbreaks, earlier relaxation of border containment measures would not have resulted in a great increase in morbidity and mortality.

EpiRegress: A Method to Estimate and Predict the Time-Varying Effective Reproduction Number.

The time-varying reproduction (Rt) provides a real-time estimate of pathogen transmissibility and may be influenced by exogenous factors such as mobility and mitigation measures which are not directly related to epidemiology parameters and observations. Meanwhile, evaluating the impacts of these factors is vital for policy makers to propose and adjust containment strategies. Here, we developed a Bayesian regression framework, EpiRegress, to provide Rt estimates and assess impacts of diverse factors on virus transmission, utilising daily case counts, mobility, and policy data. To demonstrate the method's utility, we used simulations as well as data in four regions from the Western Pacific with periods of low COVID-19 incidence, namely: New South Wales, Australia; New Zealand; Singapore; and Taiwan, China. We found that imported cases had a limited contribution on the overall epidemic dynamics but may degrade the quality of the Rt estimate if not explicitly accounted for. We additionally demonstrated EpiRegress's capability in nowcasting disease transmissibility before contemporaneous cases diagnosis. The approach was proved flexible enough to respond to periods of atypical local transmission during epidemic lulls and to periods of mass community transmission. Furthermore, in epidemics where travel restrictions are present, it is able to distinguish the influence of imported cases.

Estimating transmission dynamics of SARS-CoV-2 at different intraspatial levels in an institutional outbreak.

INTRODUCTION: Large, localised outbreaks of COVID-19 have been repeatedly reported in high-density residential institutions. Understanding the transmission dynamics will inform outbreak response and the design of living environments that are more resilient to future outbreaks. METHODS: We developed an individual-based, multilevel transmission dynamics model using case, serology and symptom data from a 60-day cluster randomised trial of prophylaxes in a densely populated foreign worker dormitory in Singapore. Using Bayesian data augmentation, we estimated the basic reproduction number and the contribution that within-room, between-level and across-block transmission made to it, and the prevalence of infection over the study period across different spatial levels. We then simulated the impact of changing the building layouts in terms of floors and blocks on outbreak size. RESULTS: We found that the basic reproduction number was 2.76 averaged over the different putative prophylaxes, with substantial contributions due to transmission beyond the residents' rooms. By the end of ~60 days of follow up, prevalence was 64.4 % (95 % credible interval 64.2-64.6 %). Future outbreak sizes could feasibly be halved by reducing the density to include additional housing blocks, or taller buildings, while retaining the overall number of men in the complex. DISCUSSION: The methods discussed can potentially be utilised to estimate transmission dynamics at any high-density accommodation site with the availability of case and serology data. The restructuring of infrastructure to reduce the number of residents per room can dramatically slow down epidemics, and therefore should be considered by policymakers as a long-term intervention.

Decreased dengue transmission in migrant worker populations in Singapore attributable to SARS-CoV-2 quarantine measures.

BACKGROUND: We examined the impact of SARS-CoV-2 social distancing and quarantine policies on dengue transmission in the general and migrant worker populations in Singapore. METHODS: We utilized all nationally reported dengue cases in the general and migrant worker populations from 1 January 2013 to 31 May 2020. A difference-in-difference identification strategy was used to determine the effects of social distancing and quarantine policies on reported dengue case counts over time, whilst controlling for weather patterns, seasonality, age and population size. RESULTS: A reduction of 4.8 dengue cases per age band among migrant workers was attributable to quarantine policies, corresponding to a total reduction of around 432 reported dengue cases over 10 weeks. In the general working population, an increase of 14.5 dengue cases per age band was observed, which corresponds to a total increase of around 1450 reported dengue cases in the same time period. There is an expected relative risk reduction in dengue transmission for the migrant worker population at 0.635 due to quarantine policy and a relative risk increase for the general working population due to social distancing policies at 0.685. CONCLUSIONS: Migrant workers experienced a reduced risk of dengue when they were confined to their dormitories as part of the COVID-19 social distancing measures. Our study highlights the vulnerability of migrant workers under normal working conditions.

Determining environmental and anthropogenic factors which explain the global distribution of Aedes aegypti and Ae. albopictus.

BACKGROUND: Responsible for considerable global human morbidity and mortality, Aedes aegypti and Ae. albopictus are the primary vectors of several important human diseases, including dengue and yellow fever. Although numerous variables that affect mosquito survival and reproduction have been recorded at the local and regional scales, many remain untested at the global level, potentially confounding mapping efforts to date. METHODS: We develop a modelling ensemble of boosted regression trees and maximum entropy models using sets of variables previously untested at the global level to examine their performance in predicting the global distribution of these two vectors. The results show that accessibility, absolute humidity and annual minimum temperature are consistently the strongest predictors of mosquito presence. Both vectors are similar in their response to accessibility and humidity, but exhibit individual profiles for temperature. Their mapped ranges are therefore similar except at peripheral latitudes, where the range of Ae. albopictus extends further, a finding consistent with ongoing trapping studies. We show that variables previously identified as being relevant, including maximum and mean temperatures, enhanced vegetation index, relative humidity and population density, are comparatively weak performers. RESULTS: The variables identified represent three key biological mechanisms. Cold tolerance is a critical biological parameter, controlling both species' distribution northwards, and to a lesser degree for Ae. albopictus which has consequent greater inland suitability in North America, Europe and East Asia. Absolute humidity restricts the distribution of both vectors from drier areas, where moisture availability is very low, and increases their suitability in coastal areas. The latter is exacerbated by accessibility with increased likelihood of vector importation due to greater potential for human and trade movement. CONCLUSION: Accessibility, absolute humidity and annual minimum temperatures were the strongest and most robust global predictors of Ae. aegypti and Ae. albopictus presence, which should be considered in control efforts and future distribution projections.

Empirical evidence of the public health benefits of tropical forest conservation in Cambodia: a generalised linear mixed-effects model analysis.

BACKGROUND: Potential synergies between public health and environmental protection that offer new opportunities for achieving health and sustainable development targets have been postulated. However, empirical evidence of the effect of ecosystem degradation and protection on public health outcomes is scarce, which restricts policy makers' ability to assess the net health effects of land-use change. METHODS: We used generalised linear mixed-effects models to analyse data for 35 547 households in 1766 communities from the Cambodian Demographic Health Surveys to investigate the relation between health and protected areas across deforestation gradients in Cambodia between Feb 1, 2005, and April 30, 2014. Diarrhoea, acute respiratory infection, and fever in children younger than 5 years were used as population health indicators. Dense and mixed forest coverage were derived from Open Development Cambodia, and forest loss was calculated from 2000 to 2004, 2004 to 2009, and 2009 to 2014. The incidence of non-specific illness and injury in people older than 15 years was used as a negative control. Our analyses included rich pseudo-panel data (combining cross-sectional datasets from 2005, 2010, and 2014) that accounted for socioeconomic, demographic, and behavioural characteristics, and had a negative control, approximating a quasi-experimental study design. FINDINGS: Deforestation of dense forest was associated with an increased incidence of diarrhoea (p=0·007), fever (p=0·0495), and acute respiratory infection in children (p=0·003). For example, a 10 percentage point increase in loss of dense forest was estimated to be associated with an increase of 14·1% (95% CI 2·6-35·8) in the incidence of diarrhoea in children younger than 5 years per household in the 2 weeks before the Cambodian Demographic Health Surveys. Protected area coverage, but not type, was associated with decreased incidences of diarrhoea (p=0·028) and acute respiratory infection (p=0·030). Apart from an association between mixed forest coverage and increased incidence of diarrhoea, forest coverage was not associated with any health outcomes. INTERPRETATION: Deforestation is associated with increased risk of several major sources of global childhood morbidity and mortality. Although causal mechanisms are unclear, our findings suggest that protected areas could help to alleviate the global health burden, presenting new possibilities for simultaneous achievement of public health and conservation goals. FUNDING: Ministry of Education of Singapore.