Title: Dengue fever transmission between construction site and its 1 surrounding communities in China 2 Running transmission between construction site and communities 3

39 Background: Due to more mosquito habitats and the lack of basic mosquito control facilities, 40 construction sites are more likely to have secondary cases after case importation, which may 41 increase the number of cases in the neighborhood community and the chance of community 42 transmission. This study aims to investigate how to effectively reduce the dengue transmission 43 in construction sites and the neighboring communities. 44 Methods: Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model of 45 human and SEI model of mosquitoes were developed to estimate the transmission of dengue 46 virus between human and mosquitoes within the construction site and within a neighboring 47 community, as well between them. With the calibrated model, we further estimated the 48 effectiveness of different intervention scenarios targeting at reducing the transmissibility at 49 different locations (i.e. construction sites and community) with the total attack rate (TAR) and 50 the duration of the outbreak (DO). 51 Results: A total of 102 construction site-related and 131 community-related cases of dengue 52 were reported in our study area. Without intervention, the cases related to the construction site 53 and the community rose to 156 (TAR: 31.25%) and 10796 (TAR: 21.59%). When cutting off 54 the transmission route from mosquitoes to human in the community, the community cases 55 decreased to a minimum of 33 compared with other simulated scenarios (TAR: 0.068%, DO: 56 60 days). If the transmission route from infectious mosquitoes in the community, and from the 57 construction site to susceptible people on the site, was cut off at the same time, the cases in the 58 construction site dropped to a minimum of 74 (TAR: 14.88%, DO: 66 days). 59 Conclusions: To control the outbreak effectively for both the construction site and the 60 community, interventions needed to be taken within the community and from the community 61 to the construction site. If interventions were only taken within the construction site, this could 62 not reduce the number of cases on the construction site. If interventions were taken within the 63 construction site or between the construction site and the community, this could not lead to a 64 reduction in the number of cases in the community.

[1]  M. Ghosh,et al.  Mathematical analysis of reinfection and relapse in malaria dynamics , 2020, Appl. Math. Comput..

[2]  Jin Qin,et al.  The long-term changing dynamics of dengue infectivity in Guangdong, China, from 2008-2018: a modelling analysis. , 2019, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[3]  J. Rui,et al.  Incidence dynamics and investigation of key interventions in a dengue outbreak in Ningbo City, China , 2019, PLoS neglected tropical diseases.

[4]  Samson Olaniyi.  Dynamics of Zika Virus Model with Nonlinear Incidence and Optimal Control Strategies , 2018, Applied Mathematics & Information Sciences.

[5]  L. Ng,et al.  Construction sites as an important driver of dengue transmission: implications for disease control , 2018, BMC Infectious Diseases.

[6]  Tao Liu,et al.  The epidemiological characteristics and molecular phylogeny of the dengue virus in Guangdong, China, 2015 , 2018, Scientific Reports.

[7]  W. Cao,et al.  Spatiotemporal responses of dengue fever transmission to the road network in an urban area. , 2018, Acta tropica.

[8]  L. Luo,et al.  Molecular evidence for new sympatric cryptic species of Aedes albopictus (Diptera: Culicidae) in China: A new threat from Aedes albopictus subgroup? , 2018, Parasites & Vectors.

[9]  V. Louis,et al.  Investigating spatio-temporal distribution and diffusion patterns of the dengue outbreak in Swat, Pakistan. , 2017, Journal of infection and public health.

[10]  Zhen Jin,et al.  The Driving Force for 2014 Dengue Outbreak in Guangdong, China , 2016, PloS one.

[11]  Peng Gong,et al.  Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model , 2016, PLoS neglected tropical diseases.

[12]  M. Boots,et al.  How Important is Vertical Transmission of Dengue Viruses by Mosquitoes (Diptera: Culicidae)? , 2015, Journal of Medical Entomology.

[13]  Xiaobo Liu,et al.  Dengue is still an imported disease in China: a case study in Guangzhou. , 2015, Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases.

[14]  Andrew J Tatem,et al.  The changing epidemiology of dengue in China, 1990-2014: a descriptive analysis of 25 years of nationwide surveillance data , 2015, BMC Medicine.

[15]  Qiyong Liu,et al.  Dengue fever in China , 2015, The Lancet.

[16]  Tao Wang,et al.  Evaluation of Inapparent Dengue Infections During an Outbreak in Southern China , 2015, PLoS neglected tropical diseases.

[17]  S. Kalayanarooj,et al.  Advances in the understanding, management, and prevention of dengue. , 2015, Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology.

[18]  Andrea L. Caprara,et al.  Entomological impact and social participation in dengue control: a cluster randomized trial in Fortaleza, Brazil , 2015, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[19]  Bin Chen,et al.  Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability , 2014, PloS one.

[20]  P. Verdonschot,et al.  Flight distance of mosquitoes (Culicidae): A metadata analysis to support the management of barrier zones around rewetted and newly constructed wetlands , 2014 .

[21]  M. Petzold,et al.  Community-centred eco-bio-social approach to control dengue vectors: an intervention study from Myanmar , 2012, Pathogens and global health.

[22]  Michael A. Johansson,et al.  The Incubation Periods of Dengue Viruses , 2012, PloS one.

[23]  N. Hens,et al.  Dynamic Epidemiological Models for Dengue Transmission: A Systematic Review of Structural Approaches , 2012, PloS one.

[24]  Xiao-Guang Chen,et al.  A local outbreak of dengue caused by an imported case in Dongguan China , 2012, BMC Public Health.

[25]  A. James,et al.  Dengue Fever in mainland China. , 2010, The American journal of tropical medicine and hygiene.

[26]  H M Yang,et al.  Assessing the effects of temperature on the population of Aedes aegypti, the vector of dengue , 2009, Epidemiology and Infection.

[27]  San Martín,et al.  The Epidemiology of Dengue in the Americas Over the Last Three Decades , 2008 .

[28]  E Massad,et al.  Modelling the control strategies against dengue in Singapore , 2007, Epidemiology and Infection.

[29]  Charly Favier,et al.  Influence of spatial heterogeneity on an emerging infectious disease: the case of dengue epidemics , 2005, Proceedings of the Royal Society B: Biological Sciences.

[30]  Birgit H B Van Benthem,et al.  Spatial patterns of and risk factors for seropositivity for dengue infection. , 2005, The American journal of tropical medicine and hygiene.

[31]  L. P. Lounibos,et al.  Dispersal of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in an urban endemic dengue area in the State of Rio de Janeiro, Brazil. , 2003, Memorias do Instituto Oswaldo Cruz.

[32]  C. Donnelly,et al.  The seasonal pattern of dengue in endemic areas: mathematical models of mechanisms. , 2002, Transactions of the Royal Society of Tropical Medicine and Hygiene.

[33]  L. Esteva,et al.  Influence of vertical and mechanical transmission on the dynamics of dengue disease. , 2000, Mathematical biosciences.

[34]  Repka Rs,et al.  The driving force. , 1987, CDA journal.

[35]  Miguel A. Melgarejo,et al.  Fuzzy model identification of dengue epidemic in Colombia based on multiresolution analysis , 2014, Artif. Intell. Medicine.

[36]  D. Otranto,et al.  Mosquitoes (Diptera: Culicidae). , 2013 .