Measuring the effects of COVID-19-related disruption on dengue transmission in southeast Asia and Latin America: a statistical modelling study

Bangladesh records persistently increased number of dengue deaths in recent years: Dissecting the shortcomings and means to resolve

Objectives

Dengue, a life-threatening disease caused by the mosquito-borne dengue virus, has become a severe problem in recent years in Bangladesh, a South Asian country. In this study, we have critically analyzed the factors contributing to the escalation of the dengue burden in recent years in Bangladesh and discussed the strategies for effective control.

Design

This retrospective observational study analyzed the dengue data collected from the five most dengue-affected countries (Bangladesh, Brazil, Mexico, Peru, and the Philippines) from 2019 to 2023.

Results

An increased number of dengue-related deaths has been recorded in Bangladesh since 2021. The year 2023 has witnessed a record high dengue-related deaths in Bangladesh, with cumulative deaths for the year surpassing all totals of the previous 23 years (2000-2022: 853 deaths vs 2023: 1705 deaths). Comparing the epidemiologic data of major dengue-endemic countries over the last 5 years, Bangladesh recorded higher dengue fatality rates consecutively for 3 years. Besides the environmental and viral host factors, which are also applicable to many other dengue-endemic countries, there is concern about the failures and mismanagement of authorities to manage dengue patients properly.

Conclusion

This study provided evidence that Bangladesh recorded higher dengue fatality rates in recent years. By implementing multi-pronged proactive approaches that can ensure proper prevention programs and appropriate patient management, Bangladesh or similar other countries can significantly reduce the current dengue burden and the associated deaths.

Efficacy and safety of Butantan-DV in participants aged 2-59 years through an extended follow-up: results from a double-blind, randomised, placebo-controlled, phase 3, multicentre trial in Brazil

BACKGROUND

A single-dose dengue vaccine that protects individuals across a wide age range and regardless of dengue serostatus is an unmet need. We assessed the safety and efficacy of the live, attenuated, tetravalent Butantan-dengue vaccine (Butantan-DV) in adults, adolescents, and children. We previously reported the primary and secondary efficacy and safety endpoints in the initial 2 years of follow-up. Here we report the results through an extended follow-up period, with an average of 3·7 years of follow-up.

METHODS

In this double-blind, randomised, placebo-controlled, phase 3, multicentre trial in Brazil, healthy participants (aged 2-59 years) who had not previously received a dengue vaccine were enrolled and randomly assigned 2:1 (stratified by age 18-59 years, 7-17 years, and 2-6 years) using a central electronic randomisation system to receive 0·5 mL of Butantan-DV (containing approximately 103 plaque-forming units of each of the four vaccine virus strains) or placebo, administered subcutaneously. Syringes containing vaccine or placebo were prepared by an unmasked trial pharmacist who was not involved in any subsequent participant assessments; other site staff and the participants remained unaware of the group allocations. Vaccine efficacy was calculated with the accrual of virologically confirmed dengue (VCD) cases (by RT-PCR) at least 28 days after vaccination up until the cutoff (at least 2 years of follow-up from the last participant enrolled). The primary endpoint was vaccine efficacy against VCD after day 28 by any dengue virus (DENV) serotype regardless of dengue serostatus at baseline in the per-protocol population. The primary and secondary safety endpoints up until day 21 were previously reported; secondary safety endpoints include the frequency of unsolicited vaccine-related adverse events after day 22. Safety analyses were done on all participants as treated. This trial is registered with ClinicalTrials.gov (NCT02406729) and is ongoing.

FINDINGS

Of 16 363 participants assessed for eligibility, 16 235 were randomly assigned between Feb 22, 2016, and July 5, 2019, and received single-dose Butantan-DV (10 259 participants) or placebo (5976 participants). 16 162 participants (Butantan-DV n=10 215; placebo n=5947) were included in the per-protocol population and 16 235 (Butantan-DV n=10 259; placebo n=5976) in the safety population. At the data cutoff (July 13, 2021), participants had 2-5 years of follow-up (mean 3·7 years [SD 1·0], median 4·0 years [IQR 3·2-4·5]). 356 VCD cases were captured through the follow-up (128 in the vaccine group and 228 in the placebo group). Vaccine efficacy against VCD caused by any DENV serotype was 67·3% (95% CI 59·4-73·9); cases caused by DENV-3 or DENV-4 were not observed. The proportions of participants who had serious adverse events were similar between treatment groups (637 [6·2%] in the vaccine group and 395 [6·6%] in the placebo group) up until the cutoff.

INTERPRETATION

A single dose of Butantan-DV was generally well tolerated and efficacious against symptomatic VCD (caused by DENV-1 and DENV-2) for a mean of 3·7 years. These findings support the continued development of Butantan-DV to prevent dengue disease in children, adolescents, and adults regardless of dengue serostatus.

FUNDING

Instituto Butantan and Merck Sharp & Dohme LLC, a subsidiary of Merck & Co.

TRANSLATIONS

For the Spanish and Portuguese translations of the abstract see Supplementary Materials section.

Effect of single-dose, live, attenuated dengue vaccine in children with or without previous dengue on risk of subsequent, virologically confirmed dengue in Cebu, the Philippines: a longitudinal, prospective, population-based cohort study

BACKGROUND

A three-dose dengue vaccine (CYD-TDV) was licensed for use in children aged 9 years and older starting in 2015 in several dengue-endemic countries. In 2016, the Philippine Department of Health implemented a dengue vaccination programme, which was discontinued because of safety concerns. We assessed the relative risk of developing virologically confirmed dengue among children who did or did not receive a single dose of CYD-TDV by previous dengue virus (DENV) infections at baseline classified as none, one, and two or more infections.

METHODS

In this longitudinal, prospective, population-based cohort study, we enrolled healthy children (aged 9-14 years) residing in Bogo or Balamban, Cebu, Philippines, between May 2, and June 2, 2017, before a mass dengue vaccination campaign, via the Rural Health Unit in Bogo and three Rural Health Units in Balamban. We collected demographic information and sera for baseline DENV serostatus and conducted active surveillance for acute febrile illness. Children who developed acute febrile illness were identified, clinical data were collected, and blood was drawn for confirmation of dengue by RT-PCR. The primary outcome was the relative risk of developing virologically confirmed dengue among children who received or did not receive a single dose of CYD-TDV by DENV serostatus at baseline.

FINDINGS

A single dose of CYD-TDV did not confer protection against virologically confirmed dengue in children who had none or one previous DENV infection at baseline. One dose conferred significant protection against hospital admission for virologically confirmed dengue among participants who had two or more previous DENV infections at baseline during the first 3 years (70%, 95% CI 20-88; p=0·017) and the entire follow-up period (67%, 19-87; p=0·016).

INTERPRETATION

The risk of developing virologically confirmed dengue after a single dose of CYD-TDV varied by baseline DENV serostatus. Since the study assessed the effect of only a single dose, the findings cannot inform decisions on vaccination by public health officers. However, the findings have implications for children who receive an incomplete vaccination regimen and these results should prompt more detailed analyses in future trials on dengue vaccines.

FUNDING

The Philippine Department of Health, Hanako Foundation, WHO, Swedish International Development Cooperation Agency, International Vaccine Institute, University of North Carolina, and US National Institute of Allergy and Infectious Diseases.

Epidemiological Characteristics of Overseas-Imported Infectious Diseases Identified through Airport Health-Screening Measures: A Case Study on Fuzhou, China

BACKGROUND

This study aimed to examine the epidemiological characteristics of imported infections and assess the effectiveness of border health screening in detecting imported diseases.

METHODS

We obtained infection data for 2016 to 2019 from the Fuzhou Changle International Airport Infection Reporting System. The demographic, temporal, and spatial characteristics of travel-related infections were analyzed using r×c contingency tables, the Cochran-Armitage trend test, and seasonal-trend decomposition using LOESS (STL). Detection rates were used as a proxy for the effectiveness of border health-screening measures.

RESULTS

Overall, 559 travel-related infections were identified during the study period, with 94.3% being imported infections. Airport health screening demonstrated an overall effectiveness of 23.7% in identifying travel-associated infections. Imported infections were predominantly identified in males, with 55.8% of cases occurring in individuals aged 20-49. The peak periods of infection importation were from January to February and from May to August. The infectious diseases identified were imported from 25 different countries and regions. All dengue fever cases were imported from Southeast Asia. Most notifiable infections (76.0%) were identified through fever screening at the airport.

CONCLUSION

The increasing number of imported infections poses a growing challenge for public health systems. Multifaceted efforts including surveillance, vaccination, international collaboration, and public awareness are required to mitigate the importation and spread of infectious diseases from overseas sources.

Serosurveillance of dengue infection and correlation with mosquito pools for dengue virus positivity during the COVID-19 pandemic in Tamil Nadu, India - A state-wide cross-sectional cluster randomized community-based study

Background

Dengue is a vector-borne viral disease impacting millions across the globe. Nevertheless, akin to many other diseases, reports indicated a decline in dengue incidence and seroprevalence during the COVID-19 pandemic (2020-22). This presumably could be attributed to reduced treatment-seeking rates, under-reporting, misdiagnosis, disrupted health services and reduced exposure to vectors due to lockdowns. Scientific evidence on dengue virus (DENV) disease during the COVID-19 pandemic is limited globally.

Methods

A cross-sectional, randomized cluster sampling community-based survey was carried out to assess anti-dengue IgM and IgG and SARS-CoV-2 IgG seroprevalence across all 38 districts of Tamil Nadu, India. The prevalence of DENV in the Aedes mosquito pools during 2021 was analyzed and compared with previous and following years of vector surveillance for DENV by real-time PCR.

Findings

Results implicate that both DENV-IgM and IgG seroprevalence and mosquito viral positivity were reduced across all the districts. A total of 13464 mosquito pools and 5577 human serum samples from 186 clusters were collected. Of these, 3·76% of mosquito pools were positive for DENV. In the human sera, 4·12% were positive for DENV IgM and 6·4% were positive for DENV IgG. The anti-SARS-CoV-2 antibody titres correlated with dengue seropositivity with a significant association whereas vaccination status significantly correlated with dengue IgM levels.

Interpretation

Continuous monitoring of DENV seroprevalence, especially with the evolving variants of the SARS-CoV-2 virus and surge in COVID-19 cases will shed light on the transmission and therapeutic attributes of dengue infection.

Human movement and environmental barriers shape the emergence of dengue

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Impacts of social deprivation on mortality and protective effects of greenness exposure in Hong Kong, 1999-2018: A spatiotemporal perspective

Addressing health inequality is crucial for fostering healthy city development. However, there is a dearth of literature simultaneously investigating the effects of social deprivation and greenness exposure on mortality risks, as well as how greenness exposure may mitigate the adverse effect of social deprivation on mortality risks from a spatiotemporal perspective. Drawing on socioeconomic, remote sensing, and mortality record data, this study presents spatiotemporal patterns of social deprivation, population weighted greenness exposure, and all-cause and cause-specific mortality in Hong Kong. A Bayesian regression model was applied to investigate the impacts of social deprivation and greenness exposure on mortality and examine how socioeconomic inequalities in mortality may vary across areas with different greenness levels in Hong Kong from 1999 to 2018. We observed a decline in social deprivation (0.67-0.56), and an increase in greenness exposure (0.34-0.41) in Hong Kong during 1999-2018. Areas with high mortality gradually clustered in the Kowloon Peninsula and the northern regions of Hong Kong Island. Adverse impacts of social deprivation on all-cause mortality weakened in recent years (RR from 2009 to 2013: 1.103, 95%CI: 1.051-1.159, RR from 2014 to 2018: 1.041 95%CI: 0.950-1.139), while the protective impacts of greenness exposure consistently strengthened (RR from 1999 to 2003: 0.903, 95%CI: 0.827-0.984, RR from 2014 to 2018: 0.859, 95%CI: 0.763-0.965). Moreover, the adverse effects of social deprivation on mortality risks were found to be higher in areas with lower greenness exposure. These findings provide evidence of associations between social deprivation, greenness exposure, and mortality risks in Hong Kong over the past decades, and highlight the potential of greenness exposure to mitigate health inequalities. Our study provides valuable implications for policymakers to develop a healthy city.

Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

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.

Unraveling varying spatiotemporal patterns of dengue and associated exposure-response relationships with environmental variables in Southeast Asian countries before and during COVID-19

The enforcement of COVID-19 interventions by diverse governmental bodies, coupled with the indirect impact of COVID-19 on short-term environmental changes (e.g. plant shutdowns lead to lower greenhouse gas emissions), influences the dengue vector. This provides a unique opportunity to investigate the impact of COVID-19 on dengue transmission and generate insights to guide more targeted prevention measures. We aim to compare dengue transmission patterns and the exposure-response relationship of environmental variables and dengue incidence in the pre- and during-COVID-19 to identify variations and assess the impact of COVID-19 on dengue transmission. We initially visualized the overall trend of dengue transmission from 2012-2022, then conducted two quantitative analyses to compare dengue transmission pre-COVID-19 (2017-2019) and during-COVID-19 (2020-2022). These analyses included time series analysis to assess dengue seasonality, and a Distributed Lag Non-linear Model (DLNM) to quantify the exposure-response relationship between environmental variables and dengue incidence. We observed that all subregions in Thailand exhibited remarkable synchrony with a similar annual trend except 2021. Cyclic and seasonal patterns of dengue remained consistent pre- and during-COVID-19. Monthly dengue incidence in three countries varied significantly. Singapore witnessed a notable surge during-COVID-19, particularly from May to August, with cases multiplying several times compared to pre-COVID-19, while seasonality of Malaysia weakened. Exposure-response relationships of dengue and environmental variables show varying degrees of change, notably in Northern Thailand, where the peak relative risk for the maximum temperature-dengue relationship rose from about 3 to 17, and the max RR of overall cumulative association 0-3 months of relative humidity increased from around 5 to 55. Our study is the first to compare dengue transmission patterns and their relationship with environmental variables before and during COVID-19, showing that COVID-19 has affected dengue transmission at both the national and regional level, and has altered the exposure-response relationship between dengue and the environment.

Exploring factors shaping antibiotic resistance patterns in Streptococcus pneumoniae during the 2020 COVID-19 pandemic

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.

Unprecedented dengue outbreak in Taiwan following COVID-19

Present study reports an unprecedented dengue outbreak in Taiwan post-COVID-19. Interrupted time series analysis reveals a significant surge after easing restrictions, emphasizing the roles of COVID-19 measures, especially travel restrictions, international transportation and climate change in the epidemic. Preventing and controlling dengue remain substantial challenges in the post-COVID-19 era.

Dengue

Dengue, caused by four closely related viruses, is a growing global public health concern, with outbreaks capable of overwhelming health-care systems and disrupting economies. Dengue is endemic in more than 100 countries across tropical and subtropical regions worldwide, and the expanding range of the mosquito vector, affected in part by climate change, increases risk in new areas such as Spain, Portugal, and the southern USA, while emerging evidence points to silent epidemics in Africa. Substantial advances in our understanding of the virus, immune responses, and disease progression have been made within the past decade. Novel interventions have emerged, including partially effective vaccines and innovative mosquito control strategies, although a reliable immune correlate of protection remains a challenge for the assessment of vaccines. These developments mark the beginning of a new era in dengue prevention and control, offering promise in addressing this pressing global health issue.

Long-term efficacy and safety of a tetravalent dengue vaccine (TAK-003): 4·5-year results from a phase 3, randomised, double-blind, placebo-controlled trial

BACKGROUND

About half of the world's population lives in dengue-endemic areas. We aimed to evaluate the long-term efficacy and safety of two doses of the tetravalent dengue vaccine TAK-003 in preventing symptomatic dengue disease of any severity and due to any dengue virus (DENV) serotypes in children and adolescents.

METHODS

In this ongoing double-blind, randomised, placebo-controlled trial, we enrolled healthy participants aged 4-16 years at 26 medical and research centres across eight dengue-endemic countries (Brazil, Colombia, Dominican Republic, Nicaragua, Panama, Philippines, Sri Lanka, and Thailand). The main exclusion criteria were febrile illness (body temperature ≥38°C) at the time of randomisation, hypersensitivity or allergy to any of the vaccine components, pregnancy or breastfeeding, serious chronic or progressive disease, impaired or altered immune function, and previous receipt of a dengue vaccine. Participants were randomly assigned 2:1 (stratified by age and region) using an interactive web response system and dynamic block assignment to receive two subcutaneous doses of TAK-003 or placebo 3 months apart. Investigators, participants, and their parents or legal guardians were blinded to group assignments. Active febrile illness surveillance and RT-PCR testing of febrile illness episodes were performed for identification of virologically confirmed dengue. Efficacy outcomes were assessed in the safety analysis set (all randomly assigned participants who received ≥1 dose) and the per protocol set (all participants who had no major protocol violations), and included cumulative vaccine efficacy from first vaccination to approximately 4·5 years after the second vaccination. Serious adverse events were monitored throughout. This study is registered with ClinicalTrials.gov, NCT02747927.

FINDINGS

Between Sept 7, 2016, and March 31, 2017, 20 099 participants were randomly assigned (TAK-003, n=13 401; placebo, n=6698). 20 071 participants (10 142 [50·5%] males; 9929 [49·5%] females; safety set) received TAK-003 or placebo, with 18 257 (91·0%) completing approximately 4·5 years of follow-up after the second vaccination (TAK-003, 12 177/13 380; placebo, 6080/6687). Overall, 1007 (placebo: 560; TAK-003: 447) of 27 684 febrile illnesses reported were virologically confirmed dengue, with 188 cases (placebo: 142; TAK-003: 46) requiring hospitalisation. Cumulative vaccine efficacy was 61·2% (95% CI 56·0-65·8) against virologically confirmed dengue and 84·1% (77·8-88·6) against hospitalised virologically confirmed dengue; corresponding efficacies were 53·5% (41·6-62·9) and 79·3% (63·5-88·2) in baseline seronegative participants (safety set). In an exploratory analysis, vaccine efficacy was shown against all four serotypes in baseline seropositive participants. In baseline seronegative participants, vaccine efficacy was shown against DENV-1 and DENV-2 but was not observed against DENV-3 and low incidence precluded evaluation against DENV-4. During part 3 of the trial (approximately 22-57 months after the first vaccination), serious adverse events were reported for 664 (5·0%) of 13 380 TAK-003 recipients and 396 (5·9%) of 6687 placebo recipients; 17 deaths (6 in the placebo group and 11 in the TAK-003 group) were reported, none were considered study-vaccine related.

INTERPRETATION

TAK-003 demonstrated long-term efficacy and safety against all four DENV serotypes in previously exposed individuals and against DENV-1 and DENV-2 in dengue-naive individuals.

FUNDING

Takeda Vaccines.

TRANSLATIONS

For the Portuguese, Spanish translations and plain language summary of the abstract see Supplementary Materials section.

Time series analysis and short-term forecasting of monkeypox outbreak trends in the 10 major affected countries

BACKGROUND

Considering the rapidly spreading monkeypox outbreak, WHO has declared a global health emergency. Still in the category of being endemic, the monkeypox disease shares numerous clinical characters with smallpox. This study focuses on determining the most effective combination of autoregressive integrated moving average model to encapsulate time dependent flow behaviour of the virus with short run prediction.

METHODS

This study includes the data of confirmed reported cases and cumulative cases from eight most burdened countries across the globe, over the span of May 18, 2022, to December 31, 2022. The data was assembled from the website of Our World in Data and it involves countries such as United States, Brazil, Spain, France, Colombia, Mexico, Peru, United Kingdom, Germany and Canada. The job of modelling and short-term forecasting is facilitated by the employment of autoregressive integrated moving average. The legitimacy of the estimated models is argued by offering numerous model performance indices such as, root mean square error, mean absolute error and mean absolute prediction error.

RESULTS

The best fit models were deduced for each country by using the data of confirmed reported cases of monkeypox infections. Based on diverse set of performance evaluation criteria, the best fit models were then employed to provide forecasting of next twenty days. Our results indicate that the USA is expected to be the hardest-hit country, with an average of 58 cases per day with 95% confidence interval of (00-400). The second most burdened country remained Brazil with expected average cases of 23 (00-130). The outlook is not much better for Spain and France, with average forecasts of 52 (00-241) and 24 (00-121), respectively.

CONCLUSION

This research provides profile of ten most severely hit countries by monkeypox transmission around the world and thus assists in epidemiological management. The prediction trends indicate that the confirmed cases in the USA may exceed than other contemporaries. Based on the findings of this study, it remains plausible to recommend that more robust health surveillance strategy is required to control the transmission flow of the virus especially in USA.

Household immunity and individual risk of infection with dengue virus in a prospective, longitudinal cohort study

Although it is known that household infections drive the transmission of dengue virus (DENV), it is unclear how household composition and the immune status of inhabitants affect the individual risk of infection. Most population-based studies to date have focused on paediatric cohorts because more severe forms of dengue mainly occur in children, and the role of adults in dengue transmission is understudied. Here we analysed data from a multigenerational cohort study of 470 households, comprising 2,860 individuals, in Kamphaeng Phet, Thailand, to evaluate risk factors for DENV infection. Using a gradient-boosted regression model trained on annual haemagglutination inhibition antibody titre inputs, we identified 1,049 infections, 90% of which were subclinical. By analysing imputed infections, we found that individual antibody titres, household composition and antibody titres of other members in the same household affect an individual's risk of DENV infection. Those individuals living in households with high average antibody titres, or households with more adults, had a reduced risk of infection. We propose that herd immunity to dengue acts at the household level and may provide insight into the drivers of the recent change in the shifting age distribution of dengue cases in Thailand.

Changing pattern of circulating dengue serotypes in the endemic region: An alarming risk to the healthcare system during the pandemic

BACKGROUND

The pandemic of COVID-19 has created an unprecedented burden on the healthcare system and medical communities resulting in new public health challenges. On the other hand, in tropical countries, another concern arises due to the similar spectrum of clinical manifestations between COVID-19 and dengue fever. Thus, the neglected tropical disease 'Dengue' writhed with more inattention. This study aims to find the effect of the COVID-19 pandemic on dengue infections in endemic areas of West Bengal, India, and their combined impact on public health. The alterations in circulating dengue serotype and their genomic diversity in different COVID-19 waves were also monitored.

METHODS

A total of 1782 patients were included in this study. Dengue NS1 ELISA, molecular serotyping, genotyping and their phylogenetic analysis were performed. GISaided analysis of various dengue serotypes and hotspot identification for risk maps of severe dengue in endemic zones were done. The burden of dengue fever and the sustainability of their viral strains with changing meteorological parameters in parallel to COVID-19 waves were analyzed.

RESULTS

Co-circulation of all the four dengue serotypes with rapid change in the pattern of prevalent serotype DENV4 (Genotype-I) in the year 2020 and DENV3 (Genotype-III) in 2021 were observed, in parallel to different circulating strains of COVID-19. Spatiotemporal distribution of DENV using Geographic Information System (GIS) applications observed a serotypic shift and hotspot mapping for risk analysis detected Kolkata as a dengue hotspot, which has also reported the maximum number of COVID-19 cases.

CONCLUSION

This study indicates the increased fitness of circulating dengue virus strains with optimal virulence as per changing environmental conditions and the inhabitant's immunity. The high infectivity rate of both the RNA viruses and considering.the consequences of severe dengue and COVID-19 in the population of the same geographical settings is an alarming risk.

D. R, Lakshmi M. I, Isvaran K, Ghosh SK, Ishtiaq F. Determinants of Aedes mosquito larval ecology in a heterogeneous urban environment- a longitudinal study in Bengaluru, India

BACKGROUND

Aedes-borne disease risk is associated with contemporary urbanization practices where city developing structures function as a catalyst for creating mosquito breeding habitats. We lack better understanding on how the links between landscape ecology and urban geography contribute to the prevalence and abundance of mosquito and pathogen spread.

METHODS

An outdoor longitudinal study in Bengaluru (Karnataka, India) was conducted between February 2021 and June 2022 to examine the effects of macrohabitat types on the diversity and distribution of larval habitats, mosquito species composition, and body size to quantify the risk of dengue outbreak in the landscape context.

FINDINGS

A total of 8,717 container breeding sites were inspected, of these 1,316 were wet breeding habitats. A total of 1,619 mosquito larvae representing 16 species from six macrohabitats and nine microhabitats were collected. Aedes aegypti and Aedes albopictus were the dominant species and significantly higher in artificial habitats than in natural habitats. Breeding preference ratio for Aedes species was high in grinding stones and storage containers. The Aedes infestation indices were higher than the WHO threshold and showed significant linear increase from Barren habitat to High density areas. We found Ae. albopictus breeding in sympatry with Ae. aegypti had shorter wing length.

CONCLUSIONS

A large proportion of larval habitats were man-made artificial containers. Landscape ecology drives mosquito diversity and abundance even at a small spatial scale which could be affecting the localized outbreaks. Our findings showed that sampling strategies for mosquito surveillance must include urban environments with non-residential locations and dengue transmission reduction programmes should focus on 'neighbourhood surveillance' as well to prevent and control the rising threat of Aedes-borne diseases.

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk

BACKGROUND

Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used.

METHODS

We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.).

RESULTS

We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures.

CONCLUSIONS

Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

Nonlinear and Multidelayed Effects of Meteorological Drivers on Human Respiratory Syncytial Virus Infection in Japan

In this study, we aimed to characterize the nonlinear and multidelayed effects of multiple meteorological drivers on human respiratory syncytial virus (HRSV) infection epidemics in Japan. The prefecture-specific weekly time-series of the number of newly confirmed HRSV infection cases and multiple meteorological variables were collected for 47 Japanese prefectures from 1 January 2014 to 31 December 2019. We combined standard time-series generalized linear models with distributed lag nonlinear models to determine the exposure-lag-response association between the incidence relative risks (IRRs) of HRSV infection and its meteorological drivers. Pooling the 2-week cumulative estimates showed that overall high ambient temperatures (22.7 °C at the 75th percentile compared to 16.3 °C) and high relative humidity (76.4% at the 75th percentile compared to 70.4%) were associated with higher HRSV infection incidence (IRR for ambient temperature 1.068, 95% confidence interval [CI], 1.056-1.079; IRR for relative humidity 1.045, 95% CI, 1.032-1.059). Precipitation revealed a positive association trend, and for wind speed, clear evidence of a negative association was found. Our findings provide a basic picture of the seasonality of HRSV transmission and its nonlinear association with multiple meteorological drivers in the pre-HRSV-vaccination and pre-coronavirus disease 2019 (COVID-19) era in Japan.

Projecting the future incidence and burden of dengue in Southeast Asia

The recent global expansion of dengue has been facilitated by changes in urbanisation, mobility, and climate. In this work, we project future changes in dengue incidence and case burden to 2099 under the latest climate change scenarios. We fit a statistical model to province-level monthly dengue case counts from eight countries across Southeast Asia, one of the worst affected regions. We project that dengue incidence will peak this century before declining to lower levels with large variations between and within countries. Our findings reveal that northern Thailand and Cambodia will show the biggest decreases and equatorial areas will show the biggest increases. The impact of climate change will be counterbalanced by income growth, with population growth having the biggest influence on increasing burden. These findings can be used for formulating mitigation and adaptation interventions to reduce the immediate growing impact of dengue virus in the region.

National dengue surveillance, Cambodia 2002-2020

Global dengue incidence has increased dramatically over the past few decades from approximately 500 000 reported cases in 2000 to over 5 million in 2019. This trend has been attributed to population growth in endemic areas, rapid unplanned urbanization, increasing global connectivity, and climate change expanding the geographic range of the Aedes spp. mosquito, among other factors. Reporting dengue surveillance data is key to understanding the scale of the problem, identifying important changes in the landscape of disease, and developing policies for clinical management, vector control and vaccine rollout. However, surveillance practices are not standardized, and data may be difficult to interpret particularly in low- and middle-income countries with fragmented health-care systems. The latest national dengue surveillance data for Cambodia was published in 2010. Since its publication, the country experienced marked changes in health policies, population demographics, climate and urbanization. How these changes affected dengue control remains unknown. In this article, we summarize two decades of policy changes, published literature, country statistics, and dengue case data collected by the Cambodia National Dengue Control Programme to: (i) identify important changes in the disease landscape; and (ii) derive lessons to inform future surveillance and disease control strategies. We report that while dengue case morbidity and mortality rates in Cambodia fell between 2002 and 2020, dengue incidence doubled and age at infection increased. Future national surveillance, disease prevention and treatment, and vector control policies will have to account for these changes to optimize disease control.

The effects of the COVID-19 pandemic on dengue cases in Malaysia

Background

Globally, the COVID-19 pandemic has affected the transmission dynamics and distribution of dengue. Therefore, this study aims to describe the impact of the COVID-19 pandemic on the geographic and demographic distribution of dengue incidence in Malaysia.

Methods

This study analyzed dengue cases from January 2014 to December 2021 and COVID-19 confirmed cases from January 2020 to December 2021 which was divided into the pre (2014 to 2019) and during COVID-19 pandemic (2020 to 2021) phases. The average annual dengue case incidence for geographical and demographic subgroups were calculated and compared between the pre and during the COVID-19 pandemic phases. In addition, Spearman rank correlation was performed to determine the correlation between weekly dengue and COVID-19 cases during the COVID-19 pandemic phase.

Results

Dengue trends in Malaysia showed a 4-year cyclical trend with dengue case incidence peaking in 2015 and 2019 and subsequently decreasing in the following years. Reductions of 44.0% in average dengue cases during the COVID-19 pandemic compared to the pre-pandemic phase was observed at the national level. Higher dengue cases were reported among males, individuals aged 20-34 years, and Malaysians across both phases. Weekly dengue cases were significantly correlated (ρ = -0.901) with COVID-19 cases during the COVID-19 pandemic.

Conclusion

There was a reduction in dengue incidence during the COVID-19 pandemic compared to the pre-pandemic phase. Significant reductions were observed across all demographic groups except for the older population (>75 years) across the two phases.

Arbovirus surveillance in pregnant women in north-central Nigeria, 2019-2022

The adverse impact of Zika (ZIKV), dengue (DENV), and chikungunya (CHIKV) virus infection in pregnancy has been recognized in Latin America and Asia but is not well studied in Africa. In Nigeria, we screened 1006 pregnant women for ZIKV, DENV and CHIKV IgM/IgG by rapid test (2019-2022). Women with acute infection were recruited for prospective study and infants were examined for any abnormalities from delivery through six months. A subset of rapid test-reactive samples were confirmed using virus-specific ELISAs and neutralization assays. Prevalence of acute infection (IgM+) was 3.8%, 9.9% and 11.8% for ZIKV, DENV and CHIKV, respectively; co-infections represented 24.5% of all infections. Prevalence in asymptomatic women was twice the level of symptomatic infection. We found a significant association between acute maternal ZIKV/DENV/CHIKV infection and any gross abnormal birth outcome (p=0.014). Further prospective studies will contribute to our understanding of the clinical significance of these endemic arboviruses in Africa.

Risk factors identification of COVID-19 patients with chronic obstructive pulmonary disease: A retrospective study in Punjab-Pakistan

BACKGROUND

Accessibility to the immense collection of studies on noncommunicable diseases related to coronavirus disease of 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an immediate focus of researchers. However, there is a scarcity of information about chronic obstructed pulmonary disease (COPD), which is associated with a high rate of infection in COVID-19 patients. Moreover, by combining the effects of the SARS-CoV-2 on COPD patients, we may be able to overcome formidable obstacles factors, and diagnosis influencers.

MATERIALS AND METHODS

A retrospective study of 280 patients was conducted at DHQ Hospital Muzaffargarh in Punjab, Pakistan. Negative binomial regression describes the risk of fixed successive variables. The association is described by the Cox proportional hazard model and the model coefficient is determined through log-likelihood observation. Patients with COPD had their survival and mortality plotted on Kaplan-Meier curves.

RESULTS

The increased risk of death in COPD patients was due to the effects of variables such as cough, lower respiratory tract infection (LRTI), tuberculosis (TB), and body-aches being 1.369, 0.693, 0.170, and 0.217 times higher at (95% confidence interval [CI]: 0.747-1.992), (95% CI: 0.231-1.156), (95% CI: 0.008-0.332), and (95% CI: -0.07 to 0.440) while it decreased 0.396 in normal condition.

CONCLUSION

We found that the symptoms of COPD (cough, LRTI, TB, and bodyaches) are statistically significant in patients who were most infected by SARS-CoV-2.

Immediate and long-term changes in infectious diseases in China at the "First-level-response", "Normalized-control" and "Dynamic-COVID-zero" stages from 2020 to 2022: a multistage interrupted-time-series-analysis

BACKGROUND

From January 2020 to December 2022, China implemented "First-level-response", "Normalized-control" and "Dynamic-COVID-zero" to block the COVID-19 epidemic; however, the immediate and long-term impact of three strategies on other infectious diseases and the difference in their impact is currently unknown. We aim to provide a more comprehensive understanding of the impact of non-pharmacological interventions (NPIs) on infectious diseases in China.

METHODS

We collected data on the monthly case count of infectious diseases in China from January 2015 to July 2022. After considering long-term trends using the Cox-Stuart test, we performed the two ratio Z tests to preliminary analyze the impact of three strategies on infectious diseases. Next, we used a multistage interrupted-time-series analysis fitted by the Poisson regression to evaluate and compare the immediate and long-term impact of three strategies on infectious diseases in China.

RESULTS

Compared to before COVID-19, the incidence of almost all infectious diseases decreased immediately at stages 1, 2, and 3; meanwhile, the slope in the incidence of many infectious diseases also decreased at the three stages. However, the slope in the incidence of all sexually transmitted diseases increased at stage 1, the slope in the incidence of all gastrointestinal infectious diseases increased at stage 2, and the slope in the incidence of some diseases such as pertussis, influenza, and brucellosis increased at stage 3. The immediate and long-term limiting effects of "Normalized-control" on respiratory-transmitted diseases were weaker than "First-level-response" and the long-term limiting effects of "Dynamic-COVID-zero" on pertussis, influenza, and hydatid disease were weaker than "Normalized-control".

CONCLUSIONS

Three COVID-19 control strategies in China have immediate and long-term limiting effects on many infectious diseases, but there are differences in their limiting effects. Evidence from this study shows that pertussis, influenza, brucellosis, and hydatid disease began to recover at stage 3, and relaxation of NPIs may lead to the resurgence of respiratory-transmitted diseases and vector-borne diseases.

Zika virus infection in European travellers returning from Thailand in 2022: A GeoSentinel case series

Zika virus is a mosquito-borne flavivirus which caused major epidemics in the Pacific and the Americas between 2013 and 2015. International travellers have previously acted as a sentinel population for Zika virus transmission in endemic areas, where local transmission may be incompletely captured by local surveillance systems. We report five recent European travellers returning from Thailand with Zika virus infection, highlighting the risk of ongoing endemic transmission in this popular tourist destination.

Singapore's 5 decades of dengue prevention and control-Implications for global dengue control

This paper summarises the lessons learnt in dengue epidemiology, risk factors, and prevention in Singapore over the last half a century, during which Singapore evolved from a city of 1.9 million people to a highly urban globalised city-state with a population of 5.6 million. Set in a tropical climate, urbanisation among green foliage has created ideal conditions for the proliferation of Aedes aegypti and Aedes albopictus, the mosquito vectors that transmit dengue. A vector control programme, largely for malaria, was initiated as early as 1921, but it was only in 1966 that the Vector Control Unit (VCU) was established to additionally tackle dengue haemorrhagic fever (DHF) that was first documented in the 1960s. Centred on source reduction and public education, and based on research into the bionomics and ecology of the vectors, the programme successfully reduced the Aedes House Index (HI) from 48% in 1966 to <5% in the 1970s. Further enhancement of the programme, including through legislation, suppressed the Aedes HI to around 1% from the 1990s. The current programme is characterised by 4 key features: (i) proactive inter-epidemic surveillance and control that is stepped up during outbreaks; (ii) risk-based prevention and intervention strategies based on advanced data analytics; (iii) coordinated inter-sectoral cooperation between the public, private, and people sectors; and (iv) evidence-based adoption of new tools and strategies. Dengue seroprevalence and force of infection (FOI) among residents have substantially and continuously declined over the 5 decades. This is consistent with the observation that dengue incidence has been delayed to adulthood, with severity highest among the elderly. Paradoxically, the number of reported dengue cases and outbreaks has increased since the 1990s with record-breaking epidemics. We propose that Singapore's increased vulnerability to outbreaks is due to low levels of immunity in the population, constant introduction of new viral variants, expanding urban centres, and increasing human density. The growing magnitude of reported outbreaks could also be attributed to improved diagnostics and surveillance, which at least partially explains the discord between rising trend in cases and the continuous reduction in dengue seroprevalence. Changing global and local landscapes, including climate change, increasing urbanisation and global physical connectivity are expected to make dengue control even more challenging. The adoption of new vector surveillance and control tools, such as the Gravitrap and Wolbachia technology, is important to impede the growing threat of dengue and other Aedes-borne diseases.

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study

BACKGROUND

Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. We sought to evaluate how such collateral impacts of COVID-19 impacted the nosocomial spread of MRB in an early pandemic context.

METHODS AND FINDINGS

We developed a mathematical model in which Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and MRB cocirculate among patients and staff in a theoretical hospital population. Responses to COVID-19 were captured mechanistically via a range of parameters that reflect impacts of SARS-CoV-2 outbreaks on factors relevant for pathogen transmission. COVID-19 responses include both "policy responses" willingly enacted to limit SARS-CoV-2 transmission (e.g., universal masking, patient lockdown, and reinforced hand hygiene) and "caseload responses" unwillingly resulting from surges in COVID-19 caseloads (e.g., abandonment of antibiotic stewardship, disorganization of infection control programmes, and extended length of stay for COVID-19 patients). We conducted 2 main sets of model simulations, in which we quantified impacts of SARS-CoV-2 outbreaks on MRB colonization incidence and antibiotic resistance rates (the share of colonization due to antibiotic-resistant versus antibiotic-sensitive strains). The first set of simulations represents diverse MRB and nosocomial environments, accounting for high levels of heterogeneity across bacterial parameters (e.g., rates of transmission, antibiotic sensitivity, and colonization prevalence among newly admitted patients) and hospital parameters (e.g., rates of interindividual contact, antibiotic exposure, and patient admission/discharge). On average, COVID-19 control policies coincided with MRB prevention, including 28.2% [95% uncertainty interval: 2.5%, 60.2%] fewer incident cases of patient MRB colonization. Conversely, surges in COVID-19 caseloads favoured MRB transmission, resulting in a 13.8% [-3.5%, 77.0%] increase in colonization incidence and a 10.4% [0.2%, 46.9%] increase in antibiotic resistance rates in the absence of concomitant COVID-19 control policies. When COVID-19 policy responses and caseload responses were combined, MRB colonization incidence decreased by 24.2% [-7.8%, 59.3%], while resistance rates increased by 2.9% [-5.4%, 23.2%]. Impacts of COVID-19 responses varied across patients and staff and their respective routes of pathogen acquisition. The second set of simulations was tailored to specific hospital wards and nosocomial bacteria (methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase producing Escherichia coli). Consequences of nosocomial SARS-CoV-2 outbreaks were found to be highly context specific, with impacts depending on the specific ward and bacteria evaluated. In particular, SARS-CoV-2 outbreaks significantly impacted patient MRB colonization only in settings with high underlying risk of bacterial transmission. Yet across settings and species, antibiotic resistance burden was reduced in facilities with timelier implementation of effective COVID-19 control policies.

CONCLUSIONS

Our model suggests that surges in nosocomial SARS-CoV-2 transmission generate selection for the spread of antibiotic-resistant bacteria. Timely implementation of efficient COVID-19 control measures thus has 2-fold benefits, preventing the transmission of both SARS-CoV-2 and MRB, and highlighting antibiotic resistance control as a collateral benefit of pandemic preparedness.

Effect of voluntary human mobility restrictions on vector-borne diseases during the COVID-19 pandemic in Japan: A descriptive epidemiological study using a national database (2016 to 2021)

The coronavirus disease 2019 (COVID-19) pandemic not only encouraged people to practice good hygiene but also caused behavioral inhibitions and resulted reduction in both endemic and imported infectious diseases. However, the changing patterns of vector-borne diseases under human mobility restrictions remain unclear. Hence, we aimed to investigate the impact of transborder and local mobility restrictions on vector-borne diseases through a descriptive epidemiological study. The analysis was conducted using data from the National Epidemiological Surveillance of Infectious Diseases system in Japan. We defined the pre-pandemic period as the period between the 1st week of 2016 to the 52nd week of 2019 and defined the pandemic period as from the 1st week of 2020 to the 52nd week of 2021, with the assumption that human mobility was limited throughout the pandemic period. This study addressed 24 diseases among notifiable vector borne diseases. Datasets were obtained from weekly reports from the National Epidemiological Surveillance of Infectious Diseases, and the incidence of each vector-borne disease was examined. Interrupted time series analysis was conducted on the epidemic curves for the two periods. Between the pre- and post-pandemic periods, the incidence of dengue fever and malaria significantly decreased, which may be related to limited human transboundary mobility (p = 0.003/0.002). The incidence of severe fever with thrombocytopenia syndrome, scrub typhus, and Japanese spotted fever did not show changes between the two periods or no association with human mobility. This study suggests that behavioral control may reduce the incidence of new mosquito-borne diseases from endemic areas but may not affect tick-borne disease epidemics within an endemic area.

Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010-2017

BACKGROUND

Dengue remains a major public health problem in the Philippines, particularly in urban areas of the National Capital Region. Thematic mapping using geographic information systems complemented by spatial analysis such as cluster analysis and hot spot detection can provide useful information to guide preventive measures and control strategies against dengue. Hence, this study was aimed to describe the spatiotemporal distribution of dengue incidence and identify dengue hot spots by barangay using reported cases from Quezon City, the Philippines from 2010 to 2017.

METHODS

Reported dengue case data at barangay level from January 1, 2010 to December 31, 2017 were obtained from the Quezon City Epidemiology and Surveillance Unit. The annual incidence rate of dengue from 2010 to 2017, expressed as the total number of dengue cases per 10,000 population in each year, was calculated for each barangay. Thematic mapping, global cluster analysis, and hot spot analysis were performed using ArcGIS 10.3.1.

RESULTS

The number of reported dengue cases and their spatial distribution varied highly between years. Local clusters were evident during the study period. Eighteen barangays were identified as hot spots.

CONCLUSIONS

Considering the spatial heterogeneity and instability of hot spots in Quezon City across years, efforts towards the containment of dengue can be made more targeted, and efficient with the application of hot spot analysis in routine surveillance. This may be useful not only for the control of dengue but also for other diseases, and for public health planning, monitoring, and evaluation.

Comparing the performance of dengue virus IgG and IgG-capture enzyme-linked immunosorbent assays in seroprevalence study

BACKGROUND

Dengue virus (DENV) is the leading cause of arboviral diseases in humans worldwide. Currently Dengvaxia, the first dengue vaccine licensed in 20 countries, was recommended for DENV seropositive individuals aged 9-45 years. Studying dengue seroprevalence can improve our understanding of the epidemiology and transmission dynamics of DENV, and facilitate future intervention strategies and assessment of vaccine efficacy. Several DENV envelope protein-based serological tests including IgG and IgG-capture enzyme-linked immunosorbent assays (ELISAs) have been employed in seroprevalence studies. Previously DENV IgG-capture ELISA was reported to distinguish primary and secondary DENV infections during early convalescence, however, its performance over time and in seroprevalence study remains understudied.

METHODS

In this study, we used well-documented neutralization test- or reverse-transcription-polymerase-chain reaction-confirmed serum/plasma samples including DENV-naïve, primary and secondary DENV, primary West Nile virus, primary Zika virus, and Zika with previous DENV infection panels to compare the performance of three ELISAs.

RESULTS

The sensitivity of the InBios IgG ELISA was higher than that of InBios IgG-capture and SD IgG-capture ELISAs. The sensitivity of IgG-capture ELISAs was higher for secondary than primary DENV infection panel. Within the secondary DENV infection panel, the sensitivity of InBios IgG-capture ELISA decreased from 77.8% at < 6 months to 41.7% at 1-1.5 years, 28.6% at 2-15 years and 0% at > 20 years (p < 0.001, Cochran-Armitage test for trend), whereas that of IgG ELISA remains 100%. A similar trend was observed for SD IgG-capture ELISA.

CONCLUSIONS

Our findings demonstrate higher sensitivity of DENV IgG ELISA than IgG-capture ELISA in seroprevalence study and interpretation of DENV IgG-capture ELISA should take sampling time and primary or secondary DENV infection into consideration.

Combined impacts of environmental and socioeconomic covariates on HFMD risk in China: A spatiotemporal heterogeneous perspective

BACKGROUND

Understanding geospatial impacts of multi-sourced influencing factors on the epidemic of hand-foot-and-mouth disease (HFMD) is of great significance for formulating disease control policies tailored to regional-specific needs, yet the knowledge is very limited. We aim to identify and further quantify the spatiotemporal heterogeneous effects of environmental and socioeconomic factors on HFMD dynamics.

METHODS

We collected monthly province-level HFMD incidence and related environmental and socioeconomic data in China during 2009-2018. Hierarchical Bayesian models were constructed to investigate the spatiotemporal relationships between regional HFMD and various covariates: linear and nonlinear effects for environmental covariates, and linear effects for socioeconomic covariates.

RESULTS

The spatiotemporal distribution of HFMD cases was highly heterogeneous, indicated by the Lorenz curves and the corresponding Gini indices. The peak time (R2 = 0.65, P = 0.009), annual amplitude (R2 = 0.94, P<0.001), and semi-annual periodicity contribution (R2 = 0.88, P<0.001) displayed marked latitudinal gradients in Central China region. The most likely cluster areas for HFMD were located in south China (Guangdong, Guangxi, Hunan, Hainan) from April 2013 to October 2017. The Bayesian models achieved the best predictive performance (R2 = 0.87, P<0.001). We found significant nonlinear associations between monthly average temperature, relative humidity, normalized difference vegetation index and HFMD transmission. Besides, population density (RR = 1.261; 95%CI, 1.169-1.353), birth rate (RR = 1.058; 95%CI, 1.025-1.090), real GDP per capita (RR = 1.163; 95%CI, 1.033-1.310) and school vacation (RR = 0.507; 95%CI, 0.459-0.559) were identified to have positive or negative effects on HFMD respectively. Our model could successfully predict months with HFMD outbreaks versus non-outbreaks in provinces of China from Jan 2009 to Dec 2018.

CONCLUSIONS

Our study highlights the importance of refined spatial and temporal data, as well as environmental and socioeconomic information, on HFMD transmission dynamics. The spatiotemporal analysis framework may provide insights into adjusting regional interventions to local conditions and temporal variations in broader natural and social sciences.

Dengue as a Disease Threatening Global Health: A Narrative Review Focusing on Latin America and Brazil

Arboviruses constitute the largest known group of viruses. These viruses are the etiological agents of pathologies known as arboviruses, with dengue being one of the most prevalent. Dengue has resulted in important socioeconomic burdens placed on different countries around the world, including those in Latin America, especially Brazil. Thus, this work intends to carry out a narrative-based review of the literature, conducted using a study of the secondary data developed through a survey of scientific literature databases, and to present the situation of dengue, particularly its distribution in these localities. Our findings from the literature demonstrate the difficulties that managers face in controlling the spread of and planning a response against dengue, pointing to the high cost of the disease for public coffers, rendering the resources that are already limited even scarcer. This can be associated with the different factors that affect the spread of the disease, including ecological, environmental, and social factors. Thus, in order to combat the disease, it is expected that targeted and properly coordinated public policies need to be adopted not only in specific localities, but also globally.

The patterns and driving forces of dengue invasions in China

BACKGROUND

Global connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China.

METHODS

We identified the local and imported cases (2006-2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling.

RESULTS

From 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio (OR) = 2.11, 95% confidence interval (CI): 1.67-2.68], Bio9 (OR = 291.62, 95% CI: 125.63-676.89), Bio15 (OR = 4.15, 95% CI: 3.30-5.24), normalized difference vegetation index in March (OR = 1.27, 95% CI: 1.06-1.51) and July (OR = 1.04, 95% CI: 1.00-1.07), and the imported cases are the major drivers of dengue local transmissions (OR = 4.79, 95% CI: 4.34-5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system.

CONCLUSIONS

Dengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization.

Assessing the Burden of Dengue during the COVID-19 Pandemic in Mexico

The transmission of the dengue virus in Mexico has historically been high, and its burden during the COVID-19 pandemic is currently not well understood. Our objective was to assess the burden of dengue-related disability-adjusted life years (DALYs) between 2020 and 2022. We conducted a cross-sectional analysis of databases resulting from an epidemiological surveillance of vector-borne diseases and computed DALYs using the protocol of the Global Burden of Disease (GBD) study 2019. Our results showed that there were 218,807 incident cases of dengue during the study period, resulting in 951 deaths. The calculated DALYs (and their 95% confidence intervals) were 8121 (7897-8396), 4733 (4661-4820), and 8461 (8344-8605) in 2020, 2021, and 2022, respectively. The DALY rates (per 100,000) were 6.5 (6.3-6.6), 3.8 (3.7-3.9), and 6.7 (6.6-6.8), respectively. The rates for 2020 and 2022 were similar to the historical mean (6.4, p = 0.884), whereas the rate for 2021 was lower than the mean. Premature mortality (years of life lost, YLL) contributed to 91% of the total burden. Our findings suggest that dengue fever remained a significant cause of disease burden during the COVID-19 pandemic, especially in terms of premature mortality.

Evolutionary dynamics of dengue virus in India

More than a hundred thousand dengue cases are diagnosed in India annually, and about half of the country's population carries dengue virus-specific antibodies. Dengue propagates and adapts to the selection pressures imposed by a multitude of factors that can lead to the emergence of new variants. Yet, there has been no systematic analysis of the evolution of the dengue virus in the country. Here, we present a comprehensive analysis of all DENV gene sequences collected between 1956 and 2018 from India. We examine the spatio-temporal dynamics of India-specific genotypes, their evolutionary relationship with global and local dengue virus strains, interserotype dynamics and their divergence from the vaccine strains. Our analysis highlights the co-circulation of all DENV serotypes in India with cyclical outbreaks every 3-4 years. Since 2000, genotype III of DENV-1, cosmopolitan genotype of DENV-2, genotype III of DENV-3 and genotype I of DENV-4 have been dominating across the country. Substitution rates are comparable across the serotypes, suggesting a lack of serotype-specific evolutionary divergence. Yet, the envelope (E) protein displays strong signatures of evolution under immune selection. Apart from drifting away from its ancestors and other contemporary serotypes in general, we find evidence for recurring interserotype drift towards each other, suggesting selection via cross-reactive antibody-dependent enhancement. We identify the emergence of the highly divergent DENV-4-Id lineage in South India, which has acquired half of all E gene mutations in the antigenic sites. Moreover, the DENV-4-Id is drifting towards DENV-1 and DENV-3 clades, suggesting the role of cross-reactive antibodies in its evolution. Due to the regional restriction of the Indian genotypes and immunity-driven virus evolution in the country, ~50% of all E gene differences with the current vaccines are focused on the antigenic sites. Our study shows how the dengue virus evolution in India is being shaped in complex ways.

Estimating the impact of the COVID-19 pandemic on dengue in Brazil

Atypical dengue prevalence was observed in 2020 in many dengue-endemic countries, including Brazil. Evidence suggests that the pandemic disrupted not only dengue dynamics due to changes in mobility patterns, but also several aspects of dengue surveillance, such as care seeking behavior, care availability, and monitoring systems. However, we lack a clear understanding of the overall impact on dengue in different parts of the country as well as the role of individual causal drivers. In this study, we estimated the gap between expected and observed dengue cases in 2020 using an interrupted time series design with forecasts from a neural network and a structural Bayesian time series model. We also decomposed the gap into the impacts of climate conditions, pandemic-induced changes in reporting, human susceptibility, and human mobility. We find that there is considerable variation across the country in both overall pandemic impact on dengue and the relative importance of individual drivers. Increased understanding of the causal mechanisms driving the 2020 dengue season helps mitigate some of the data gaps caused by the COVID-19 pandemic and is critical to developing effective public health interventions to control dengue in the future.

Rapid Appraisals of the Transformation Strategy Required to Sustain Dengue Vector Control During and After the COVID-19 Pandemic in Indonesia

Purpose

This research aimed to observe the gap for improvement in dengue vector control during COVID-19, considering two stakeholders: the government and society. We formulated two research questions: 1) How is the government managing dengue vector control during the COVID-19 pandemic? 2) What is the situation of dengue disease, its vectors, and vector control in the community?

Methods

This study uses multiple approaches: policy review, social listening using Twitter analysis, and interviews. A policy review was employed to capture the journey of dengue vector control in Indonesia from dengue found in Indonesia until the COVID-19 pandemic. Twitter data captured public opinions through social media about dengue and vector control. Interviews involved program implementers that consider knowing the situation in the field of dengue and its vector control. The informant was selected through purposive sampling.

Results

To control dengue disease, the Indonesian government has released regulations about dengue vector control that adjusts the COVID-19 situation, but vector control is still not running optimally, resulting in the data supply for policy not running well.

Conclusion

Dengue cases continued during the COVID-19 pandemic, even in some places stated an outbreak occurred. Vector control does not work correctly during the COVID-19 pandemic due to social restrictions. It is recommended to encourage the implementation of community empowerment through one house, one jumantik, which is equipped with self-reporting to mitigate and respond to similar situations as the pandemic.

Correlations between COVID-19 and dengue obtained via the study of South America, Africa and Southeast Asia during the 2020s

A dramatic increase in the number of outbreaks of dengue has recently been reported, and climate change is likely to extend the geographical spread of the disease. In this context, this paper shows how a neural network approach can incorporate dengue and COVID-19 data as well as external factors (such as social behaviour or climate variables), to develop predictive models that could improve our knowledge and provide useful tools for health policy makers. Through the use of neural networks with different social and natural parameters, in this paper we define a Correlation Model through which we show that the number of cases of COVID-19 and dengue have very similar trends. We then illustrate the relevance of our model by extending it to a Long short-term memory model (LSTM) that incorporates both diseases, and using this to estimate dengue infections via COVID-19 data in countries that lack sufficient dengue data.

Editorial: Infectious Disease Epidemiology and Transmission Dynamics

Infectious diseases, such as COVID-19 [...].

Identification of Hazard and Socio-Demographic Patterns of Dengue Infections in a Colombian Subtropical Region from 2015 to 2020: Cox Regression Models and Statistical Analysis

Dengue is a disease of high interest for public health in the affected localities. Dengue virus is transmitted by Aedes species and presents hyperendemic behaviors in tropical and subtropical regions. Colombia is one of the countries most affected by the dengue virus in the Americas. Its central-west region is a hot spot in dengue transmission, especially the Department of Antioquia, which has suffered from multiple dengue outbreaks in recent years (2015-2016 and 2019-2020). In this article, we perform a retrospective analysis of the confirmed dengue cases in Antioquia, discriminating by both subregions and dengue severity from 2015 to 2020. First, we conduct an exploratory analysis of the epidemic data, and then a statistical survival analysis is carried out using a Cox regression model. Our findings allow the identification of the hazard and socio-demographic patterns of dengue infections in the Colombian subtropical region of Antioquia from 2015 to 2020.

Real world data study of prevalence and direct costs related to dengue management in Brazil's private healthcare from 2015 to 2020

BACKGROUND

The burden of dengue in Brazil is poorly documented and is based on data from the public health care setting. This study estimated the prevalence and costs of dengue management in the private health care system in Brazil from 2015 to 2020 using a large claims database from Orizon.

METHODS

We selected claims with dengue ICD codes (ICD-10 A90 or A91) from January 2015 to December 2020. Prevalence was estimated based on the population enrolled in health insurance plans in the given year. Costs were adjusted for the inflation up to December 2021 and evaluated by measures of central tendency and dispersion.

RESULTS

A total of 63,882 unique beneficiaries were included, with a total of 64,186 dengue cases. The year with the highest prevalence was 2015 (1.6% of patients who used health plans), and there was also an increase in cases in 2016 and 2019. The median cost per hospitalization in 2015 was US$486.17, and in 2020, it reached US$696.72. The median cost of a case seen at an emergency room ranged from US$ 97.78 in 2015 to US$ 118.16 in 2017.

CONCLUSIONS

The estimated prevalence of dengue in this population of private health-insured patients followed the epidemiological trends of the general population in Brazil, with the highest rates in 2015, 2016, and 2019. The cost of dengue management has increased in the private health care setting over the years.

COVID-19 and dengue coinfection in Latin America: A systematic review

Introduction

Methods

Results

Conclusion

Dengue Incidence and Aedes Vector Collections in Relation to COVID-19 Population Mobility Restrictions

Contrary to expectation, dengue incidence decreased in many countries during the period when stringent population movement restrictions were imposed to combat COVID-19. Using a seasonal autoregressive integrated moving average model, we previously reported a 74% reduction in the predicted number of dengue cases from March 2020 to April 2021 in the whole of Sri Lanka, with reductions occurring in all 25 districts in the country. The reduction in dengue incidence was accompanied by an 87% reduction in larval collections of Aedes vectors in the northern city of Jaffna. It was proposed that movement restrictions led to reduced human contact and blood feeding by Aedes vectors, accompanied by decreased oviposition and vector densities, which were responsible for diminished dengue transmission. These findings are extended in the present study by investigating the relationship between dengue incidence, population movement restrictions, and vector larval collections between May 2021 and July 2022, when movement restrictions began to be lifted, with their complete removal in November 2021. The new findings further support our previous proposal that population movement restrictions imposed during the COVID-19 pandemic reduced dengue transmission primarily by influencing human–Aedes vector interaction dynamics.

Dengue vaccine development: challenges and prospects

PURPOSE OF REVIEW

Dengue vaccine development is a high public health priority. To date, no dengue vaccine is in widespread use. Here we review the challenges in dengue development and the latest results for the second-generation dengue vaccines.

RECENT FINDINGS

The biggest hurdle is the immunological interaction between the four antigenically distinct dengue serotypes. The advantages of second-generation dengue vaccines are the inclusion of nonstructural proteins of the dengue backbone and a more convenient dosing with reduced numbers of doses needed.

SUMMARY

Although dengue-primed individuals can already benefit from vaccination with the first licensed dengue vaccine CYD-TDV, the public health need for the dengue-naive population has not yet been met. The urgent need remains to identify correlates of both protection and enhancement; until such correlates have been identified, all second-generation dengue vaccines still need to go through full phase 3 trials. The 5-year efficacy and safety data for both second-generation dengue vaccines are imminent.