Dengue fever (DF) is caused by four distinct serotypes of dengue virus (DENV-I, DENV-II, DENV-III, and DENV-IV) (Flavivirade
) which are transmitted by Aedes aegypti
and Aedes albopictus
]. DF has become the most important vector-borne disease in the tropical and sub-tropical regions, mainly circulating in Latin America, Southeast Asia, and South Asia [2
]. More than 390 million cases are reported annually [1
]. Severe dengue infection can be mediated through an antibody-dependent enhancement (ADE) mechanism which can induce dengue hemorrhagic fever or dengue shock syndrome [3
]. The risk of severe dengue infection could be elevated if the secondary infection is caused by a different serotype of dengue virus.
The transmission risk of DF could be influenced by multiple environmental risk factors. Climatic conditions, including temperature, precipitation, and humidity, are the major drivers which have been highlighted in previous studies [4
]. Higher temperatures could play a crucial role in shortening the duration of the mosquito’s life cycle or the extrinsic incubation period (EIP) of the virus, resulting in an increase of mosquito abundance and transmission probability as well [7
]. An appropriate amount of precipitation is required to create more habitats for the mosquito vector [8
]. Moreover, the increasing number of artificial containers produced by humans [10
], alongside the requisite rainfall, also affords the Aedes
spp. mosquito an increased survival [4
In addition to climate drivers, socio-economic characteristics and landscape-level variables also have different impacts on dengue transmission [14
]. A previous study conducted in Thailand indicated that irrigated fields or orchards near households could increase the transmission risk of dengue [15
]. In Kenya, an irrigated area had higher dengue seroprevalence rates than areas without irrigation [16
]. Population density played the most important role in the dengue transmission rate in Swat, Pakistan [17
]. Those environmental factors affected the spatial and temporal distributions of both vector abundance and disease transmission [18
]. Thus, it is very important to understand the spatial and temporal diffusion patterns of dengue transmission and its relevant environmental conditions as prevention resources can be deployed in the disease hotspots.
Dengue outbreaks have occurred in Taiwan every year since the early 1990s, and are usually ignited by imported cases of the virus from endemic countries [20
]. The scale of an outbreak is determined by vector abundance and climate conditions in that year. Southern Taiwan, including Kaohsiung City and Tainan City, is a major dengue hotspot due to suitable climate conditions and high population density within the metropolitan regions. Earlier studies have focused on the dengue epidemics in Kaohsiung City because most cases have been reported from that area. Tainan City, considered to be the second largest dengue hotspot in southern Taiwan, experienced a dengue outbreak in 2015; however, studies relevant to this outbreak are still very rare. A previous study from southern Taiwan demonstrated that the El Niño Southern Oscillation (ENSO) index and local elevated temperature during spring and summer might be associated with the most recent outbreaks [21
]. The spatial and temporal patterns of dengue transmission during this outbreak are seldom studied in detail.
This study conducts a spatial epidemiological analysis of the 2015 dengue outbreak in the metropolitan region of Tainan City. There are three objectives in this study: (1) to explore the basic epidemiological features of the 2015 dengue outbreak in the metropolitan region of Tainan City; (2) to evaluate the occurrence of space-time clusters of the dengue outbreak; (3) to explore associations between specific land cover/land use (LCLU) types and the dengue incidence rate. The findings of this study could benefit public health agencies and workers in Tainan City in terms of future dengue outbreak control/prevention measures.
The global burden of DF has rapidly increased since 1990, and many countries in Southeast Asia (including Taiwan) have experienced annual outbreaks [2
]. Most previous studies of dengue outbreaks in Taiwan have focused on the major epidemic center in Kaohsiung City [37
]. This is the first study to evaluate the epidemiological characteristics and spatial-temporal patterns of dengue incidence rates in Tainan City. A fundamental difference in the age and age-gender distribution trends for dengue transmission was observed. In most dengue endemic countries in Southeast Asian and Latin American, children are typically considered the most vulnerable group [40
]. Guo et al. analyzed dengue outbreaks in Guangdong (China) from 2005–2011, and found that the highest incidence rate was observed in the young adult population (20–30 years old) [43
]. Similar to the patterns in Taiwan, dengue outbreaks in Singapore also exhibit an increasing incidence with age [44
]. The different epidemiological characteristics might be related to several environmental determinants, economic development statuses, and interactions between humans and vectors. The higher dengue infection rate among the elderly population in Tainan City could raise a critical issue related to comorbidities. Dengue infection with other chronic conditions, like cardiovascular disease or diabetes, could exacerbate the progression of DF and increase the mortality rate [45
]. Thus, disease prevention work should be strengthened among such vulnerable populations.
To our knowledge, this is the first time a report on the reverse pattern of age–gender distributions of dengue infection has been presented. Two hypotheses could be derived from such an observation. First, the transmission risk, which is mediated through the environmental or behavioral characteristics, might be higher in the senior female population and cause higher infection rates in the study area. The other hypothesis might be associated with physiological or immunological responses. Older females might demonstrate a higher symptomatic infection rate than elderly males, so they have a higher chance of being reported by the physicians. Both of these hypotheses are worthy of further investigation.
The spatial and temporal pattern of the dengue outbreak in Tainan City shows a clear north-south direction. The outbreak originated in the North district and then spread to the West-Central and South districts. The major hotspot in September was clustered within the West-Central district, which is the oldest community with many ancient buildings and a high population density in the city. On the other hand, the most populated East district is a relatively newly developed area where the higher dengue incidence rate occurred in the later stage (October) of the outbreak. The risk maps highlight the important areas where public health workers should enhance control efforts in the future.
The spatial and temporal analysis of DF highlights the significant association with population density, which is also linked to the higher percentage of residential area derived from the results of the spatial regression model. The association between dengue and urbanized characteristics or population density has been mentioned in other studies [48
]. One study, which applied the boosted regression trees approach, indicated that human settlements and waterbodies are major risk factors for dengue cases in Malaysia [51
]. The link is mediated through vector abundance and contact probability of the human host. Our study further demonstrates that the association is non-linear. A moderate percentage (about 40%) of the residential area has a stronger association with a higher dengue incidence rate. One study has also shown such a non-linear pattern between dengue outbreak and population density in the Pearl River Delta, China [52
]. The non-linear association might be attributed to the complicated interactions between vector activity and human behaviors, which include people movements, personal protective awareness, or response to the health education, in a finer environmental setting. Vector control also played an important role to control the scale of the outbreak. The percentage of wetland also exhibited the non-linear pattern with dengue incidence; however, the wetland is mainly in the suburban or coastal region within the Annan and Anping districts where the dengue incidence rate is relatively lower than the city center.
The outbreak in Tainan could have been triggered by the unusual climate factors which have been proved by our previous work [21
]. With the increasing effects of climate change, similar outbreaks could occur again in the future. Our study provides a preliminary result showing dengue diffusion patterns in space and time. Public health workers can focus on the potential hotspots in order to strengthen disease/vector control measures. The vulnerable population can also take more preventive activities through community education to reduce the risk of infection.
The limitation in the study is that regular vector surveillance data is not available in the study region. The impact of different environmental determinants on the vector population is therefore unknown. There is also no way to analyze the spatial and temporal relationships between dengue incidence and vector population dynamics. Routine vector surveillance systems can help public health workers to monitor vector abundance in a longitudinal way, which more accurately identifies the level of dengue transmission risk [53
]. The Taiwan CDC and the national health research institutes have started to develop an intelligent mosquito trap, which might provide the opportunity for establishing a vector surveillance system in the future.