Aug 2026· PLoS Neglected Tropical Diseases· Vol 20, pp. e0014521· 0 citations· 49 references
Medicine
TL;DR
This study provides a practical, evidence-based tool for health authorities to prioritize interventions in at-risk hub cities by identifying vector control and the reduction of mosquito biting rates as the most critical factors influencing transmission dynamics of dengue.
Abstract
Background A dramatic increase in dengue infections has been observed in recent years, raising concerns regarding the potential further spread of dengue. Shenzhen, a major international port city in China, is typically a non-endemic region; however, it faces persistent risks from imported cases. The resurgence of imported risk has made the identification of effective prevention and control strategies a pressing public health priority for the region. Methodology We integrated epidemic, environmental, and intervention data from Shenzhen covering the period from 2015 to 2023. A compartmental mathematical model was developed to characterize the transmission dynamics of dengue triggered by imported cases. We applied sensitivity analysis and developed a quantitative metric to evaluate the relative efficacy of various non-pharmaceutical intervention strategies in this specific urban context. Findings Our sensitivity analysis identified vector control and the reduction of mosquito biting rates as the most critical factors influencing transmission dynamics. These analytical results were further validated through simulations based on a model fitted to historical data, which revealed that prioritizing these strategies significantly mitigated dengue transmission risks. Compared to alternative measures, these targeted interventions demonstrated a substantially higher impact on reducing the risk and scale of local outbreaks. Conclusions This study provides a practical, evidence-based tool for health authorities to prioritize interventions in at-risk hub cities. Our findings underscore that for non-endemic port cities like Shenzhen, focusing on rigorous vector management and biting rate reduction is critical for mitigating the risk of dengue epidemics. These insights offer a strategic framework for guiding future epidemic control efforts against vector-borne diseases in non-endemic urban environments.
The indispensable role of rigorous mathematical modeling is underscored in guiding dengue preparedness, optimizing control strategies, and strengthening epidemic response capacity in resource-limited settings by integrating epidemiological data with advanced numerical modeling.
Objectives Dengue fever is a major global public health concern. While China has not yet established stable, local transmission of the disease, imported cases frequently lead to local dengue epidemics throughout the year. This paper aims to outline the characteristics of dengue outbreaks in China between 2005 and 2023. Methods We collected literature on dengue in China from various databases and extracted relevant data for analysis. This data included patients’ sociodemographic characteristics, serotype composition, and clinical manifestations, which we then summarized and compared, evaluating the relationship between dengue virus (DENV) serotypes and clinical manifestations, and analyzing the monthly and regional distribution patterns of dengue fever cases based on case data obtained from the China Public Science and Health Data Center (CPC). Results In the included studies, the ratio of male to female was approximately 1:1, The age group with the highest proportion of dengue patients is those aged 30 to 39. Their occupations were predominantly business service, and the predominant serotype of the infection was DENV-1, followed by DENV-2. The major clinical signs and symptoms in dengue patients were fever, asthenia, and headache. Patients infected with DENV-1, 3 were associated with some specific clinical phenotypes. Dengue cases typically peak between September and October each year. Although these cases are primarily concentrated in the southern regions of China, there is a noticeable trend of increasing incidence in northern areas over time. Conclusions This study offers an in-depth examination of the molecular epidemiology, clinical characteristics, and the seasonal and geographic distribution of dengue cases in China from 2005 to 2023. The findings provide valuable insights for future research on dengue epidemics.
Kun Peng, Xiao-Dan Huang, Peng-Xiang Huang et al.· Frontiers in Cellular and In...· 0 citations
Background Dengue is a major public health challenge, and predictive models are crucial for early warning systems. However, many current modeling practices rely exclusively on climatic factors or employ complex algorithms that lack the interpretability needed for informed public health decision-making. To address these shortcomings, we developed and validated a multidimensional, interpretable statistical model to predict monthly dengue incidence. Methodology/Principal Findings We used a Generalized Linear Mixed Model (GLMM) with a Negative Binomial distribution to analyze 14 years (2010-2023) of spatiotemporal data from 37 municipalities in Huila, Colombia, an endemic region. The model integrates non-linear and lagged effects of climatic, demographic, and socioeconomic factors. The final model underwent rigorous external validation on an independent test set (2021-2023). Our model demonstrated high predictive discrimination (R2 = 0.743, Spearman's {rho} = 0.657), accurately capturing the timing of epidemic outbreaks. Key findings include the identification of an optimal thermal window for transmission at 27-28{degrees}C, a threshold effect for precipitation above 800 mm, and a saturation dynamic in outbreak autocorrelation. Conclusions/Significance This mechanistically-informed statistical approach provides a robust and transparent tool for epidemiological surveillance, successfully balancing high predictive performance with the explanatory power needed for effective, data-driven public health interventions.
N. Luna-Martinez, E. X. Cruz-Rodríguez, E. A. Bernal-Castro· medRxiv· 0 citations
Dengue fever poses a significant global public health threat, and its effective management requires a comprehensive approach to control the dengue prevalence. This study proposes an optimal control problem for the dengue transmission, incorporating three key control measures: information‐induced self‐protection, saturated treatment, and pesticide use for vector control, and is analyzed using Pontryagin's Maximum Principle. Importantly, a novel higher nonlinearity in the cost construction is incorporated. Seven distinct control policies ( P1−P7$$ {P}_1-{P}_7 $$ ) incorporating different combinations of control measures are designed and evaluated through numerical simulations. The results demonstrate that the combined strategy of all controls (Policy P7$$ {P}_7 $$ ) is the most effective, reducing infection prevalence to minimal levels within approximately 60 days, while maintaining sustained control thereafter. In comparison, the combined use of information and treatment (Policy P4$$ {P}_4 $$ ) achieves a similar outcome but requires nearly 120 days to stabilize the infection. Among single‐control strategies, information‐induced self‐protection (Policy P1$$ {P}_1 $$ ) outperforms treatment ( P2$$ {P}_2 $$ ) and pesticide application ( P3$$ {P}_3 $$ ) when applied alone. Cost‐effectiveness analysis using CCER, IAR, and ICER reveals that Policy P1$$ {P}_1 $$ is the most cost‐effective intervention, with the lowest CCER value, while Policy P7$$ {P}_7 $$ averts the highest number of infections. Furthermore, the analysis shows that the control's effectiveness depends strongly on epidemic severity: for mild outbreaks ( R0≤2.5$$ {R}_0\le 2.5 $$ ), combined strategies such as P4$$ {P}_4 $$ and P6$$ {P}_6 $$ (treatment and pesticide) perform efficiently, whereas for severe outbreaks ( R0>2.5$$ {R}_0>2.5 $$ ), comprehensive control ( P7$$ {P}_7 $$ ) becomes essential. Additionally, delayed implementation of control measures significantly worsens disease outcomes, increasing infection peaks and economic burden. Overall, the study highlights the importance of timely and integrated intervention strategies and provides quantitative insights for optimal resource allocation in dengue control.
Manisha, Anuj Kumar, Sun-Mi Lee et al.· Optimal control applications...· 0 citations
Cost-effectiveness analysis using infection averted ratio (IAR), average cost-effectiveness ratio (ACER), and incremental cost-effectiveness ratio (ICER) reveals that the combined implementation of all six control measures (Strategy 9) is most cost-effective, averting 9,200 infections (35.38% reduction) at an ACER of 3,756.536.
Francis Agono, G. Acheneje, B. C. Agbata et al.· European Journal of Statisti...· 0 citations
A deterministic climate-driven SEAIR-SEI malaria transmission model that includes the impact of temperature, rainfall, and humidity on mosquito biology and endogenous community awareness is developed that can serve as an efficient and affordable framework for malaria control in sub-Saharan Africa.
R. N. Nyabwanga, L. K. Ketter, A. N. Osogo et al.· medRxiv· 0 citations
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