Abstract
Background
Dengue fever, a viral illness spread mostly by Aedes mosquitoes, continues to pose a substantial public health issue in Dhaka city, Bangladesh. In Dhaka, climatic and socio-demographic factors like population density affect the spread of dengue. The dengue indexes are greatest in the residential mixed zone. Numerous environmental parameters, such as temperature, relative humidity, rainfall, and the air pollution index, have been linked to mosquito larvae, and dengue prevalence is correlated with urbanization, decreased vegetation, and population expansion.
Methods
By using an extensive dataset that encompasses a range of years, we use spatial and temporal analytic methodologies to investigate the correlation between land use attributes, climatic variables, and the occurrence of dengue fever. To better understand the dynamics of dengue, the built environment and climatic factors are treated as independent variables in this study. ArcPy is a Python package that facilitates here for geographic data analysis and ArcMap 10.7 also used for visualizing spatial data.
Results
The results of our study demonstrate that land use significantly influences the spatial patterns of Dengue incidence in Dhaka city. The dengue hotspot Thana are identified and these are Badda, Jatrabari, kadamtali, Mirpur, Mohammadpur, Sobujbagh, Shyampur, Tejgoan, Dhanmondi and Uttara. All of these areas’ population density and residential use as land use is higher than the other Thana of Dhaka city. There exists a significant correlation between climatic characteristics, such as temperature (0.25), rainfall (.803), specific humidity (0.74), relative humidity (0.76), wind speed (0.4) and Dengue incidence patterns. This research emphasizes the structural use and climatic relationship in Dengue epidemics, with climatic conditions playing a significant role as drivers of these variations.
Conclusions
This research demonstrates the complex relationship between land use, meteorological factors, and the spread of Dengue fever in Dhaka city. The results of this study have significant significance for several domains, including urban planning, public health measures, and vector control tactics. A comprehensive understanding of the temporal and geographical patterns of dengue transmission might aid in the development of accurate and effective prevention measures intended to lessen the effects of dengue in cities, such as Dhaka.
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Background
Dengue fever burden and transmission dynamics may vary as a result of climate change. Research indicates that the dengue virus may become less widespread as temperatures increase (Mendoza-Cano et al. 2023). However, under some temperature profiles, there is an increased risk of possible dengue epidemics; the biggest risk is associated with temperatures between 27 and 31 °C (Trejo et al. 2023). Climate change is likely to broaden the geographic range of dengue transmission, with temperature, relative humidity, and rainfall being significant climatic parameters associated with dengue transmission (Bhatia et al. 2022). Proactive steps can help reduce the health implications of climate change, which influence infectious illnesses in humans at different scales (Souza et al. 2021). Climate change is expected to have an impact on dengue infections in Bangladesh, where outbreaks might happen at any moment and the season could last all year (Paul et al. 2021).
A virus called dengue is carried by mosquitoes and has been reported to be present around the world, especially in South Asia and especially in Bangladesh. Every year, Bangladesh has had many dengue epidemics of differing severity. Bangladesh experienced its worst dengue epidemic to date in 2019, with a notable number of cases and fatalities (Kayesh et al. 2023). There are a number of variables, including geography, population density, and climate change, that affect the spread of dengue throughout South Asia, including Bangladesh (Islam et al. 2023). In Bangladesh, the dengue virus (DENV) is widely distributed and co-circulating in all four serotypes, which raises the possibility of developing severe dengue (Banerjee and Robinson 2023). Climate variables like temperature, humidity, precipitation, wind speed, and air pressure might affect the spread of dengue (Kamal et al. 2023). In order to stop dengue epidemics, vector control methods are essential, and Bangladesh has to develop better vector control plans (Miah et al. 2023). Controlling the spread of dengue in Bangladesh and other South Asian nations may be accomplished by comprehending the effects of climatic conditions and putting appropriate control measures in place.
Climate and the incidence of dengue are intricately linked. The most significant explanatory factors for the transmission of dengue virus (DENV) between vectors and human hosts are rainfall, temperature, and humidity, according to a meta-analysis of the literature (Depradine and Lovell 2004; Colón-González et al. 2013; Naish et al. 2014). The details of these interactions, however, differ greatly between locations and are still mostly unclear from the available research. Furthermore, a number of empirical research conducted in Asia and Latin America have cautioned that there may not be a linear link between precipitation and dengue prevalence since excessive rainfall might have a detrimental effect on vector reproduction (Halide and Ridd 2008; Wu et al. 2009). Furthermore, artificial water containers have a critical role in both dengue incidence and Aedes mosquito reproduction, particularly in metropolitan settings and in built up area (Islam et al. 2019).
Dengue, a viral disease transmitted by the Aedes mosquito, is mainly prevalent in tropical and subtropical regions of the globe (Nyenke et al. 2023). This highly infectious disease is caused by dengue virus that shows symptoms like fever, rash, and joint pain (Sinare and Barkade 2023). Without the need for an incubation period (Li et al. 2023), this dengue virus has not only been rapidly transmitted in tropical urban areas, but also in rural ones (Man et al. 2023), which is influenced by multiple factors, such as mosquito population density, climatic conditions, and population movement patterns (Zeng et al. 2023). Today, this potential worldwide epidemic (Mukherji and Kaushik 2015) is spreading from the USA to China, from Europe to Australia, and even in Japan, Colombia, and Venezuela (Aliaga-Samanez et al. 2021). In a nutshell, South America, Africa, and Southeast Asia are mainly the hotspots of dengue outbreaks, with over 105 million worldwide estimated dengue infections every year (Cattarino et al. 2020). Over 2.5 billion people across 100 countries around the globe are currently under threat of this dengue virus (Dehghani and Kassiri 2021), and Bangladesh, a Southeast Asian tropical country, is not an exception.
Once known as ‘Dhaka Fever’ (Kamal et al. 2023), dengue epidemiology in Bangladesh has exhibited a consistent pattern of increasing frequency and size of outbreaks and a gradual expansion in geographic scope since its initial recorded outbreak in 2000 (Hossain et al. 2023a). Currently, the incidence of the dengue virus is extensive across Bangladesh, substantially impacting morbidity and mortality rates (Bhowmik et al. 2023), especially in Dhaka (Alam 2023). According to the World Health Organization (2023), dengue is now an epidemic in Dhaka, and Dhaka city corporation has been the most severely affected among the areas in Dhaka division. Several researches have been conducted in Dhaka city to explore the reasons for the dengue outbreak in Dhaka city.
Kamal et al. (2023) explored that higher ground and air temperatures, lesser vegetation, water bodies, dense urban characteristics, relative humidity, and precipitation positively impact dengue, also argued by (Banu et al. 2014; Islam et al. 2021; Paul et al. 2018; Salje et al. 2016; Sharmin et al. 2015; Zahirul Islam et al. 2018). Hossain et al. (2023b) stated that maximum and minimum temperature, humidity, and wind speed have a positive relation with dengue, however, dengue cases decreased with higher levels of rainfall (Hossain et al. 2023b). Salje et al. (2016) also argued that most cases occur between June and November, with a strong correlation between increased rainfall and Dengue cases occurring two months later. Monthly precipitation days substantially correlate with dengue prevalence (Rahman et al. 2020). Dengue transmission in Dhaka is influenced by temperature fluctuations, and socio-demographic factors like population density (Sharmin et al. 2015). Haque et al. (2023) stated that the central business and residential mixed zone has the highest dengue indices, and age distribution is a highly significant risk factor. Paul et al. (2018) identified that tires, plastic drums, discarded construction materials, refrigerator trays, vehicle parts, container location, presence of vegetation, and availability of shade for containers significantly impact the abundance of dengue mosquitoes. Additionally, a notable increase in the prevalence of Aedes mosquitoes in low socioeconomic areas of Dhaka. (Paul et al. 2018).
According to Guo et al. (2023), in China, temperature, number of rainy days, pan evaporation, relative humidity, and sea level pressure have positive impact on dengue fever, and wind speed is a protective factor. In India, poorer, high-density areas, warmer temperatures increase the risk of dengue (Telle et al. 2021). Besides, both temperature and precipitation play crucial roles in virus development and mosquito population dynamics (Mutheneni et al. 2017). Ahmad et al. (2018) found that there were correlations between mosquito larvae and various environmental factors, including rainfall, relative humidity, temperature, and air pollution index, and dengue prevalence relate to urbanization, reduced vegetation, and population growth, but not water bodies in Malaysia (Zan 2015). Insufficient flood control and water disposal infrastructure can heighten the likelihood of a dengue outbreak, particularly in densely populated regions (Junaid Tahir et al. 2020). Ebi and Nealon (2016) also stated that global dengue risk is strongly influenced by local temperature, precipitation, urbanization, and socioeconomic factors with that urban expansion will increase the frequency and intensity of dengue outbreaks (Lindsay et al. 2017).
As there was not sufficient research on dengue of Dhaka city, besides, the dengue outbreak condition of Dhaka city is severe, this research aims to examine the factors influencing the transmission and spread of dengue fever in Dhaka. Specifically, it will investigate the relationship between meteorological factors and dengue, as well as the relationship between the built environment and dengue.
Materials and methods
This research takes a quantitative approach, and it examines the meteorological data and Landuse based detail data of Dhaka city in order to better understand the dynamics of dengue (Table 1).
Variables and methods of analysis
Methods
According to Codecademy Team (2023), Numpy and Pandas, are very powerful and open-source python libraries, used for data extraction and analysis in this research. Microsoft excel is used for data visualization. ArcPy is a Python package that facilitates geographic data analysis, conversion, management, and map automation using Python, is used for spatial analysis, besides, ArcMap 10.7 also used for visualizing spatial data. Jupyter Notebook is a web-based interactive computing platform and IDLE a Python's Integrated Development and Learning Environment both are used for scripting python language.
Study area
Dhaka city, a residence of 23,210,000 people (Dhaka, Bangladesh Metro Area Population 1950–2024 | MacroTrends 2024) is selected as the study area, where dengue is severely outbroken. For exploring the relationship between dengue patients and climate factors, Dhaka city is fully considered as a study area, and for the built environment, the study followed dengue hotspot zones (DHZ) explored by The Directorate General of Health Services (DGHS).
According to DGHS Fig. 1 illustrates the dengue hotspots in Dhaka city, which include Jatrabari, Mugda, Kodomtoli, Jurain, Dhanmondi, Basabo, Uttara, Mohammadpur, Mirpur, Tejgaon, and Badda (Dhaka Tribune 2023). The Thana boundaries, small jurisdiction boundaries of the dengue hotspot areas, are considered for spatial analysis, and the Thanas are Badda, Dhanmondi, Jatrabari, Kadomtoli, Mirpur, Mohammadpur, Sabujbag, Shaympur, Tejgaon, Uttara.
Data sources
Several dengue data were collected from the website of the Directorate General of Health Services (DGHS) (dghs.gov.bd), where daily number of dengue incidents (patients) and daily deaths due to dengue diseases is published. Hospital-based data is provided within Dhaka city and district-based data is provided all over the country. This study collected the daily hospital-based data as the focus of this study was only Dhaka city.
The POWER Project of National Aeronautics and Space Administration (NASA) (https://power.larc.nasa.gov) is the source of Meteorological Data. Time-series data (daily meteorological data) was collected following the days of the dengue incidents.
Results
Monthly dengue cases
Monthly dengue cases, spanning from September 2022 to August 2023, an increasing trend in dengue cases, despite the relatively lower values in between. Even though number of dengue cases fluctuated in the beginning. But then exhibited a sharp increase starting from May 2023. In the graph, it is evident that dengue cases typically surge during the months ranging from June to November (Fig. 2).
Structure type
Dhaka city possesses Pucca, Semi-pucca and also Katcha structures all around. It is evident that the dengue hotspot zones possess a significant amount of semi-pucca and Katcha structures. The percentage is highest in Kadamtali area which is 32.9% of semi-pucca and 32.58% of kutcha. Whereas lowest in Dhanmondi area, 27.3% of semi-pucca and 3.38% of kutcha structure (Fig. 3). On the contrary other areas of Dhaka, five areas were selected at random, shows a different picture having higher proportion of pucca structures than the other two categories (Fig. 3).
Structure use
Badda, Jatrabari, Kadamtali, Sabujbagh, and Shyampur have over 80% residential structures. Mirpur has 76.02% residential and 9.23% mixed-use, mostly residential-commercial. Dhanmondi, Mohammadpur, Tejgaon, and Uttara are around 70% residential, but also have 9.23%, 14.37%, 8.81%, and 7.87% mixed-use structures, respectively. Badda, Sabujbagh, and Shyampur have over 5% mixed-use structures. The various land uses (in percentage) in the dengue hotspot zones of Dhaka city are presented in Fig. 4. In dengue hotspots, residential use dominates, with mixed-use being mostly residential-commercial.
Residential structure use in Sher E Bangla Nagar is 70% and Cantonment is 60%. Shahbagh, Tejgaon Industrial Area, New Market is less than 50%. There have significant number of different types of structures (Fig. 5).
Residential structure use in number is higher in dengue hotspot areas than in other areas. On the contrary commercial, mixed-use, institutional, health facilities, community facilities, education and research, agricultural, miscellaneous, transportation and communication, restricted and special use structures are high in number in other areas (Fig. 6).
Land use
Land use refers to the arrangements, activities, and inputs by people to produce, change, or maintain a certain land cover type (Wang et al. 2020). Natural land use refers to the existing land including the natural distribution and arrangement of vegetation, water bodies, and other natural features on the Earth's surface. On the other hand, manmade land use refers to the manipulation of the land cover, such as agriculture, urbanization, infrastructure development, and industrial activities (Bondarenko et al. 2020; Haug 1997; Loenhart 2022). According to the Details Area Plan of Dhaka, within Dhaka city, manmade land use is divided into proposed road network, transportation and communication, overlay zone, rural settlement zone, administrative zone, institutional zone, general administrative zone, commercial zone, mixed-use zone, urban residential zone, and natural land use is divided into natural water body, natural water retention area, natural open space, natural flood flow zone (Rajdhani Unnayan Kartipakkha-RAJUK 2021).
The figure is divided into two broad categories of land use for dengue hotspot areas. The figures have been separated based on manmade land use pattern and natural land use characteristics. The first portion of the graph shows natural land use (left) in percentage and clearly states that there is no significant natural land use pattern in those areas as they are predominantly urbanized and built environments (Fig. 7).
The second portion of the graph shows manmade landuse in percentage. In terms of manmade land use, the graph highlights that “Urban residential Zone” occupies the highest percentage of land across all areas, followed by “Mixed use zone” as the second-highest. Notably, the “Mixed use Zone” combines predominantly residential and commercial units, with some also having industrial use (Fig. 7).
There is no particular land use is dominated in other areas. Each areas have its individual nature and residential land use is not predominant in New Market, Sher E Bangla Nagar, Tejgaon Industrial Area, Shahabag, Cantonment Thana (Fig. 8).
The amount of residential land use is higher in dengue hotspot areas than in other areas. Besides mixed land use percentage cannot be negligible, whereas in other areas mixed land use is lower than in dengue hotspot areas. In Dhaka city, most of the mixed land use contains residential-commercial type (Fig. 9).
Dengue and climate factors
The meteorological information for the years 2022 and 2023 has been obtained. The dataset consisted of observations collected between September 2022 and August 16, 2023, spanning a total of 350 days. Specifically, there were 122 days of data from 2022 and 228 days from 2023. The average number of Dengue cases is 8593, with a standard deviation (SD) of 4811 for the year of 2022 in Dhaka and it is calculated for the month of September to December. The smallest number of cases recorded is 2665 in December, while the greatest number is 13,984 which were in October, 2022 (Table 2). According to Table 2, the greatest number of cases in Dhaka for 2023 is reported as 28,590 only for 17 days of August 2023. The dengue data displays the average daily confirmed cases, which amount to roughly 548 for the 47 days of July and August. Additionally, the table presents the daily average values for humidity at 2 m (g/kg), relative humidity at 2 m in %, precipitation (mm/day), wind speed at 10 m (m/s), temperature, earth skin temperature and wind speed at 2 m (m/s). Based on the data, it is evident that there is an increase in both relative humidity and precipitation from the year 2022 to the year 2023 (Fig. 10) when considering the same month for comparison analysis. Furthermore, there is a strong correlation between these meteorological factors and the incidence of dengue cases (Figs. 10 and 11). The findings indicate that the minimum recorded temperature in 2022 was 16.10C, while the maximum temperature was 29.90C and in 2023 was 16.20C, while the maximum temperature was 34.90C. Furthermore, the observed precipitation ranges from a low of 0 mm/day to a high of 24.3 mm/day and 90.2 mm/day for the month of July and August, respectively, of 2023.
Correlation coefficients range from − 1 to 1, where “− 1” indicates a strong negative correlation, “1” indicates a strong positive correlation, and “0” indicates no linear correlation. Specific humidity, relative humidity and precipitation have strong positive correlation with number of dengue patients and wind speed has moderate positive correlation where land surface temperature and Air temperature have weak positive correlation (Fig. 11).
Discussion
Dengue fever incidents were reported in Bangladesh from 1964 to 1999 when there was a noticeable increase in incidence that year, which signaled the beginning of a severe outbreak that resulted in 5551 (Salje et al. 2016; Yang et al. 2023) hospitalized cases and 93 deaths (Yunus et al. 2001). Major Dengue outbreaks continued to center on Dhaka, the country's capital, until 2021 (Hossain et al. 2022). According to surveillance data gleaned from hospital records, there were seven outbreaks in Dhaka city between 2000 and 2022—each with more than 5,000 hospitalized cases. After a period of relative inactivity, dengue cases started to increase once more in 2016. This culminated in the greatest outbreak on record in 2019, with over 100,000 hospitalized patients and 179 fatalities in the Dhaka metropolis (Hossain et al. 2020). Another significant epidemic was subsequently noted in 2021, with 28,429 recorded cases and 85 fatalities; however, the concurrent COVID-19 pandemic, especially the propagation of the Delta variety (Hossain et al. 2022), may have concealed the outbreak's real scope. Notably, with 61,732 cases and 281 deaths, the second-largest outbreak happened in 2022 (https://dghs.gov.bd).
All dengue outbreaks in Bangladesh since 2000 have predominantly taken place within the confines of Dhaka city (Salje et al. 2016). Changes in the seasonal distribution of dengue cases may be related to variations in the climate. Nevertheless, due to its central location and relative compactness and flatness, Bangladesh experiences little change in climate variables like temperature and rainfall (Khatun et al. 2020). Therefore, it is likely that increased temperatures contributed to the greatest outbreak in Dhaka and may have impacted the extrinsic incubation period (EIP) of the implicated mosquitoes. Seasonal dengue virus prevalence patterns are influenced by both climatic and ecological factors, according to several academic studies (Scott and Morrison 2004). It was also determined how different environmental conditions affected dengue outbreaks (Ahmad et al. 2018; Kesetyaningsih et al. 2018). Although it is well-recognized that climate conditions affect dengue incidence, the exact association between dengue fever and climatic patterns is unclear (Gubler et al. 2001). This intricacy results from the complex life cycles of the Aedes aegypti vector and its host, both of which are very susceptible to changes in climate.
The purpose of this study was to investigate the relationships between different meteorological and built-environmental variables and dengue cases in Dhaka, Bangladesh. Based on these discovered correlations, this research sought to demonstrate the local patterns of dengue risk. This research clarifies the intricate relationships between climatic variables and land use variables that affect dengue occurrences at the local level. Previous studies have consistently emphasized the important role that humidity, rainfall, and temperature play in dengue outbreaks. The impact of these climatic factors on the occurrence of dengue is further highlighted by this study. Understanding these trends can be essential for preventing future severe dengue epidemics in Bangladesh by giving time for preparation and response actions.
According to this study, the prevalence of dengue cases can be influenced by specific climatic conditions. A rise in global temperature may increase the prevalence of vector-borne diseases (Sutherst 2004). This research found a positive association between land surface temperatures and dengue cases. Furthermore, this study found a substantial positive correlation between dengue cases and relative and specific humidity. Higher relative humidity has been associated with more dengue cases during the monsoon season because the higher humidity during this time promotes the proliferation and survival of infected mosquitoes, which aids in the spread of the virus (Barbazan et al. 2010). Rainfall was also found to affect mosquito growth in both positive and negative ways. While excessive rainfall might ruin prospective mosquito habitats, adequate rainfall supplies standing water for mosquito breeding (Medicine 2008).
The study indicated that built environments, particularly compact residential areas, and non-agricultural areas had a significant impact on the occurrence of dengue cases. Increased dengue cases were found in locations with a greater proportion of human settlements, most likely as a result of these areas' higher population densities and thus higher rates of human biting. Because of this higher biting rate, Aedes mosquitoes have more chances to bite an infected person, contract the dengue virus, and then spread the infection to others (Scott and Morrison 2010). In locations related to human activity, manmade containers were found to hold Aedes mosquito habitats, with variations noted among different types of human settlements (Vanwambeke et al. 2007). These results emphasize the value of considering land use factors when strategically designing and implementing vector control approaches.
Rainfall was also found to affect mosquito growth in both positive and negative ways. While excessive rainfall might ruin prospective mosquito habitats, adequate rainfall supplies standing water for mosquito breeding (Medicine 2008).
The study indicated that built environment, particularly compact residential areas, and non-agricultural areas had a significant impact on the occurrence of dengue cases. Increased dengue cases were found in locations with a greater proportion of human settlements, most likely as a result of these areas' higher population densities and thus higher rates of human biting. Because of this higher biting rate, Aedes mosquitoes have more chances to bite an infected person, contract the dengue virus, and then spread the infection to others (Scott and Morrison 2010). In locations related to human activity, manmade containers were found to hold Aedes mosquito habitats, with variations noted among different types of human settlements (Vanwambeke et al. 2007).
These results emphasize the value of taking land use factors into consideration when strategically designing and implementing vector control approaches.
Limitation
Although this study offers a wide range of consequences, it is crucial to recognize its inherent limitations. The main goal of the study is to understand the relationship between meteorological factors, land use features, and dengue incidence in the Dhaka area. However, a significant flaw in the dataset's design and underlying record-keeping and reporting processes is implied by the dataset's significant gaps and incompleteness. These flaws could be a result of structural problems, including an incomplete system for monitoring or a lack of awareness on the part of the responsible authorities.
Conclusions
The annual recurrence of dengue fever in Bangladesh, particularly in the urban areas of the metropolis of Dhaka, represents a continuing threat to the populace and presents ongoing difficulties for healthcare officials. Furthermore, it is important to highlight that different environmental, land use, and socioeconomic conditions that are favorable to the spread of this disease are widespread to differing degrees across the country. As a result, proactive forecasting of possible dengue outbreaks provides a crucial method for authorities to create and put into action effective plans in response to unforeseen emergencies. In this situation, incorporating health-related factors into land use planning is a determined effort to address the needs of the public's health. The main goal of this study is to clarify the intricate relationships between meteorological factors and land use patterns in relation to dengue prevalence in the urban environment of Dhaka, Bangladesh. Notably, land surface temperature, humidity, and precipitation are found to have a clearly positive impact on dengue incidence rates, while wind speed is found to have a clear and significant adverse impact. The designation of compact residential and commercial areas, structural typology, and the intended purpose of structures are only a few examples of the land use elements that have been found to exhibit a saliently positive association with dengue incidence. The conclusions drawn from this study hold enormous potential for guiding the development of policy, particularly in the context of developing a climate and land use-based early warning system customized to the distinctive epidemiological landscape of Bangladesh.
Availability of data and materials
The data will be given to anyone who requests for it.
Abbreviations
- DENV:
-
Dengue virus
- DGHS:
-
Directorate General of Health Services
- DHZ:
-
Dengue Hotspot Zones
- EIP:
-
Extrinsic Incubation Period
- NASA:
-
National Aeronautics and Space Administration
- RAJUKL:
-
Rajdhani Unnayan Kartipakkha (Development Control Authority of Dhaka)
- SD:
-
Standard deviation
References
Ahmad R, Suzilah I, Najdah WMAW, Topek O, Mustafakamal I, Lee HL (2018) Factors determining dengue outbreak in Malaysia. PLOS ONE 13(2):e0193326. https://doi.org/10.1371/journal.pone.0193326
Alam H (2023, August 19) Dengue outbreak: more cases now outside Dhaka | Dengue in Bangladesh. https://www.thedailystar.net/health/disease/news/dengue-outbreak-more-cases-now-outside-dhaka-3397446
Aliaga-Samanez A, Cobos-Mayo M, Real R, Segura M, Romero D, Fa JE, Olivero J (2021) Worldwide dynamic biogeography of zoonotic and anthroponotic dengue. PLoS Negl Trop Dis 15(6):e0009496. https://doi.org/10.1371/journal.pntd.0009496
Banerjee I, Robinson J (2023) Dengue on the rise 2022–2023: a warning for Southern Asia. Res Dev Med Med Sci 1:153–163. https://doi.org/10.9734/bpi/rdmms/v1/4674B
Banu S, Hu W, Guo Y, Hurst C, Tong S (2014) Projecting the impact of climate change on dengue transmission in Dhaka, Bangladesh. Environ Int 63:137–142. https://doi.org/10.1016/j.envint.2013.11.002
Barbazan P, Guiserix M, Boonyuan W, Tuntaprasart W, Pontier D, Gonzalez J-P (2010) Modelling the effect of temperature on transmission of dengue. Med Vet Entomol 24(1):66–73. https://doi.org/10.1111/j.1365-2915.2009.00848.x
Bhowmik KK, Ferdous J, Baral PK, Islam MS (2023) Recent outbreak of dengue in Bangladesh: a threat to public health. Health Sci Rep 6(4):e1210. https://doi.org/10.1002/hsr2.1210
Bhatia S, Bansal D, Patil S, Pandya S, Ilyas QM, Imran S (2022) A retrospective study of climate change affecting dengue: evidences, challenges and future directions. Front Public Health 10:884645. https://doi.org/10.3389/fpubh.2022.884645
Bondarenko I, Kokhan N, Gonchar O, Bondarenko B (2020) Man-made landforms in landscape design of territories as a means of solving environmental problems. Archit Civ Eng Environ 12(4):7–14. https://doi.org/10.21307/acee-2019-047
Cattarino L, Rodriguez-Barraquer I, Imai N, Cummings DAT, Ferguson NM (2020) Mapping global variation in dengue transmission intensity. Sci Transl Med 12(528):eaax4144. https://doi.org/10.1126/scitranslmed.aax4144
Codecademy Team (2023) Introduction to Pandas and NumPy. Codecademy. https://www.codecademy.com/article/introduction-to-numpy-and-pandas
Colón-González FJ, Fezzi C, Lake IR, Hunter PR (2013) The effects of weather and climate change on dengue. PLOS Negl Trop Dis 7(11):e2503. https://doi.org/10.1371/journal.pntd.0002503
Dehghani R, Kassiri H (2021) A review on epidemiology of dengue viral infection as an emerging disease. Res J Pharm Technol 14:2296–2301. https://doi.org/10.52711/0974-360X.2021.00406
Depradine C, Lovell E (2004) Climatological variables and the incidence of Dengue fever in Barbados. Int J Environ Health Res 14(6):429–441. https://doi.org/10.1080/09603120400012868
Dhaka, Bangladesh Metro Area Population 1950–2024 | MacroTrends (2024) Retrieved February 29, 2024, from https://www.macrotrends.net/cities/20119/dhaka/population
Dhaka Tribune (2023) DGHS identifies 11 dengue hotspots in Dhaka. Dhaka Tribune. https://www.dhakatribune.com/bangladesh/dhaka/319510/dghs-identifies-11-dengue-hotspots-in-dhaka
Ebi KL, Nealon J (2016) Dengue in a changing climate. Environ Res 151:115–123. https://doi.org/10.1016/j.envres.2016.07.026
Gubler DJ, Reiter P, Ebi KL, Yap W, Nasci R, Patz JA (2001) Climate variability and change in the United States: potential impacts on vector- and rodent-borne diseases. Environ Health Perspect 109(Suppl 2):223–233. https://doi.org/10.1289/ehp.109-1240669
Guo Z, Liu W, Liu X, Abudunaibi B, Luo L, Wu S, Deng B, Yang T, Huang J, Wu S, Lei L, Zhao Z, Li Z, Li P, Liu C, Zhan M, Chen T (2023) Model-based risk assessment of dengue fever transmission in Xiamen city. China Front Public Health 11:1079877. https://doi.org/10.3389/fpubh.2023.1079877
Halide H, Ridd P (2008) A predictive model for dengue hemorrhagic fever epidemics. Int J Environ Health Res 18(4):253–265. https://doi.org/10.1080/09603120801966043
Haque CE, Dhar-Chowdhury P, Hossain S, Walker D (2023) Spatial evaluation of dengue transmission and vector abundance in the city of Dhaka, Bangladesh. Geographies 3(2):268–285. https://doi.org/10.3390/geographies3020014
Haug KL (1997) The human/land dialectic. Afterimage 25(2):3–5. https://doi.org/10.1525/aft.1997.25.2.3
Hossain MS, Amin R, Mosabbir AA (2022) COVID-19 onslaught is masking the 2021 dengue outbreak in Dhaka, Bangladesh. PLOS Negl Trop Dis 16(1):e0010130. https://doi.org/10.1371/journal.pntd.0010130
Hossain MS, Noman AA, Mamun SAA, Mosabbir AA (2023a) Twenty-two years of dengue outbreaks in Bangladesh: epidemiology, clinical spectrum, serotypes, and future disease risks. Trop Med Health 51(1):37. https://doi.org/10.1186/s41182-023-00528-6
Hossain MS, Siddiqee MH, Siddiqi UR, Raheem E, Akter R, Hu W (2020) Dengue in a crowded megacity: lessons learnt from 2019 outbreak in Dhaka, Bangladesh. PLOS Negl Trop Dis 14(8):e0008349. https://doi.org/10.1371/journal.pntd.0008349
Hossain S, Islam MdM, Hasan MdA, Chowdhury PB, Easty IA, Tusar MdK, Rashid MB, Bashar K (2023b) Association of climate factors with dengue incidence in Bangladesh, Dhaka city: a count regression approach. Heliyon 9(5):e16053. https://doi.org/10.1016/j.heliyon.2023.e16053
Institute of Medicine (2008) Vector-borne diseases: understanding the environmental, human health, and ecological connections: workshop summary. In: Lemon SM, Sparling PF, Hamburg MA, Relman DA, Choffnes ER, Mack A (eds) The National Academies Press. https://doi.org/10.17226/11950
Islam S, Haque CE, Hossain S, Hanesiak J (2021) Climate variability, dengue vector abundance and dengue fever cases in Dhaka, Bangladesh: a time-series study. Atmosphere 12(7):905. https://doi.org/10.3390/atmos12070905
Islam S, Haque CE, Hossain S, Rochon K (2019) Role of container type, behavioural, and ecological factors in Aedes pupal production in Dhaka, Bangladesh: an application of zero-inflated negative binomial model. Acta Trop 193:50–59. https://doi.org/10.1016/j.actatropica.2019.02.019
Islam MA, Hasan MN, Tiwari A, Raju MAW, Jannat F, Sangkham S, Shammas MI, Sharma P, Bhattacharya P, Kumar M (2023) Correlation of Dengue and meteorological factors in Bangladesh: a public health concern. Int J Environ Res Public Health 20(6):5152. https://doi.org/10.3390/ijerph20065152
Junaid Tahir M, Rizwan Siddiqi A, Ullah I, Ahmed A, Dujaili J, Saqlain M (2020) Devastating urban flooding and dengue outbreak during the COVID-19 pandemic in Pakistan. Med J Islam Repub Iran. https://doi.org/10.47176/mjiri.34.169
Kamal ASMM, Al-Montakim MN, Hasan MA, Mitu MMP, Gazi MY, Uddin MM, Mia MB (2023) Relationship between urban environmental components and dengue prevalence in Dhaka city—an approach of spatial analysis of satellite remote sensing, hydro-climatic, and census dengue data. Int J Environ Res Public Health 20(5):3858. https://doi.org/10.3390/ijerph20053858
Kayesh MEH, Khalil I, Kohara M, Tsukiyama-Kohara K (2023) Increasing dengue burden and severe dengue risk in Bangladesh: an overview. Trop Med Infect Dis 8(1):32. https://doi.org/10.3390/tropicalmed8010032
Kesetyaningsih TW, Andarini S, Sudarto S, Pramoedyo H (2018) Determination of environmental factors affecting dengue incidence in Sleman district, Yogyakarta, Indonesia. Afr J Infect Dis 12(1 Suppl):13–25. https://doi.org/10.2101/Ajid.12v1S.3
Khatun M, Rashid M, Hygen H (2020) Climate of Bangladesh
Li H-H, Su MP, Wu S-C, Tsou H-H, Chang M-C, Cheng Y-C, Tsai K-N, Wang H-W, Chen G-H, Tang C-K, Chung P-J, Tsai W-T, Huang L-R, Yueh YA, Chen H-W, Pan C-Y, Akbari OS, Chang H-H, Yu G-Y, … Chen C-H (2023) Mechanical transmission of dengue virus by Aedes aegypti may influence disease transmission dynamics during outbreaks. Microbiology https://doi.org/10.1101/2023.03.07.531453
Lindsay SW, Wilson A, Golding N, Scott TW, Takken W (2017) Improving the built environment in urban areas to control Aedes aegypti -borne diseases. Bull World Health Organ 95(8):607–608. https://doi.org/10.2471/BLT.16.189688
Loenhart KK (2022) Architecture that bridges and merges the human-made with nature: essay one: towards a biometeorological design—architectures of the planetary invironment. In: The Routledge companion to ecological design thinking. Routledge
Man O, Kraay A, Thomas R, Trostle J, Lee GO, Robbins C, Morrison AC, Coloma J, Eisenberg JNS (2023) Characterizing dengue transmission in rural areas: a systematic review. PLoS Negl Trop Dis 17(6):e0011333. https://doi.org/10.1371/journal.pntd.0011333
Mendoza-Cano O, Trujillo X, Huerta M, Ríos-Silva M, Lugo-Radillo A, Benites-Godínez V, Bricio-Barrios JA, Ríos-Bracamontes EF, Uribe-Ramos JM, Baltazar-Rodríguez GM, Murillo-Zamora E (2023) Assessing the relationship between annual surface temperature changes and the burden of dengue: implications for climate change and global health outcomes. Trop Med Infect Dis 8(7):351. https://doi.org/10.3390/tropicalmed8070351
Miah MM, Jannat SN, Rahman MR, Arafat Y, Pingki FH (2023) Assessing the impact of climatic factors on dengue fever transmission in Bangladesh. https://doi.org/10.21203/rs.3.rs-2503817/v1
Mukherji S, Kaushik SK (2015) Dengue: a runaway epidemic and a bewildered public health worker. Med J Armed Forces India 71(1):3–4. https://doi.org/10.1016/j.mjafi.2014.12.002
Mutheneni SR, Morse AP, Caminade C, Upadhyayula SM (2017) Dengue burden in India: recent trends and importance of climatic parameters. Emerg Microbes Infect 6(1):1–10. https://doi.org/10.1038/emi.2017.57
Naish S, Dale P, Mackenzie JS, McBride J, Mengersen K, Tong S (2014) Climate change and dengue: a critical and systematic review of quantitative modelling approaches. BMC Infect Dis 14(1):1–14. https://doi.org/10.1186/1471-2334-14-167
Nyenke CU, Nnokam BA, Esiere RK, Nwalozie R (2023) Dengue fever: etiology, diagnosis, prevention and treatment. Asian J Res Infect Dis 14(1):26–33. https://doi.org/10.9734/ajrid/2023/v14i1279
Paul KK, Dhar-Chowdhury P, Haque CE, Al-Amin HM, Goswami DR, Kafi MAH, Drebot MA, Lindsay LR, Ahsan GU, Brooks WA (2018) Risk factors for the presence of dengue vector mosquitoes, and determinants of their prevalence and larval site selection in Dhaka, Bangladesh. PLOS ONE 13(6):e0199457. https://doi.org/10.1371/journal.pone.0199457
Paul KK, Macadam I, Green D, Regan DG, Gray RT (2021) Dengue transmission risk in a changing climate: Bangladesh could experience a longer dengue fever season in the future. bioRxiv 2021–2025. https://doi.org/10.1101/2021.05.24.443300
Rahman KM, Sharker Y, Rumi RA, Khan M-UI, Shomik MS, Rahman MW, Billah SM, Rahman M, Streatfield PK, Harley D, Luby SP (2020) An association between rainy days with clinical dengue fever in Dhaka, Bangladesh: findings from a hospital based study. Int J Environ Res Public Health 17(24):9506. https://doi.org/10.3390/ijerph17249506
RAJUK (2021) Rajdhani Unnayan Kartipakkha. Detail area plan of Dhaka, pp 2016–2035
Salje H, Morales I, Gurley ES, Saha S (2016) Seasonal distribution and climatic correlates of dengue disease in Dhaka, Bangladesh. Am J Trop Med Hyg 94(6):1359–1361. https://doi.org/10.4269/ajtmh.15-0846
Scott TW, Morrison A (2004) Aedes aegypti density and the risk of dengue-virus transmission. Ecol Aspects Appl Genet Modif Mosquitoes 2:187–206
Scott TW, Morrison AC (2010) Longitudinal field studies will guide a paradigm shift in dengue prevention. In: Atkinson PW (ed) Vector biology, ecology and control. Springer, Dordrecht, pp 139–161. https://doi.org/10.1007/978-90-481-2458-9_10
Sharmin S, Glass K, Viennet E, Harley D (2015) Interaction of mean temperature and daily fluctuation influences dengue incidence in Dhaka, Bangladesh. PLOS Negl Trop Dis 9(7):e0003901. https://doi.org/10.1371/journal.pntd.0003901
Sinare AB, Barkade GD (2023) Dengue: a mosquito borne disease. World J Biol Pharm Health Sci 14(2):251–261. https://doi.org/10.30574/wjbphs.2023.14.2.0218
Souza AD, Abreu MC, Oliveira-Júnior JF (2021) Impact of climate change on human infectious diseases: dengue. Braz Arch Biol Technol 64:e21190502. https://doi.org/10.1590/1678-4324-2021190502
Sutherst RW (2004) Global change and human vulnerability to vector-borne diseases. Clin Microbiol Rev 17(1):136–173. https://doi.org/10.1128/CMR.17.1.136-173.2004
Telle O, Nikolay B, Kumar V, Benkimoun S, Pal R, Nagpal BN, Paul RE (2021) Social and environmental risk factors for dengue in Delhi city: a retrospective study. PLoS Negl Trop Dis 15(2):e0009024. https://doi.org/10.1371/journal.pntd.0009024
Trejo I, Barnard M, Spencer JA, Keithley J, Martinez KM, Crooker I, Hengartner N, Romero-Severson EO, Manore C (2023) Changing temperature profiles and the risk of dengue outbreaks. PLOS Climate 2(2):e0000115. https://doi.org/10.1371/journal.pclm.0000115
Turney S (2022) Pearson correlation coefficient (r) | guide and examples. Scribbr. https://www.scribbr.com/statistics/pearson-correlation-coefficient/
Vanwambeke SO, Lambin EF, Eichhorn MP, Flasse SP, Harbach RE, Oskam L, Somboon P, Van Beers S, Van Benthem BHB, Walton C, Butlin RK (2007) Impact of land-use change on dengue and malaria in Northern Thailand. EcoHealth 4(1):37–51. https://doi.org/10.1007/s10393-007-0085-5
Wang D, Fu Y, Wang P, Huang B, Lu C-T (2020) Reimagining city configuration: automated urban planning via adversarial learning. In: Proceedings of the 28th international conference on advances in geographic information systems, pp 497–506. https://doi.org/10.1145/3397536.3422268
World Health Organization (2023) Dengue—Bangladesh. https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON481
Wu PC, Lay JG, Guo HR, Lin CY, Lung SC, Su HJ (2009) Higher temperature and urbanization affect the spatial patterns of dengue fever transmission in subtropical Taiwan. Sci Total Environ 407(7):2224–2233. https://doi.org/10.1016/j.scitotenv.2008.11.034
Yang J, Mosabbir AA, Raheem E, Hu W, Hossain MS (2023) Demographic characteristics, clinical symptoms, biochemical markers and probability of occurrence of severe dengue: a multicenter hospital-based study in Bangladesh. PLoS Negl Trop Dis 17(3):e0011161. https://doi.org/10.1371/journal.pntd.0011161
Yunus E, Bangali A, Ataul M, Mahmood H, Rahman M, Chowdhury A, Talukder K (2001) Dengue outbreak 2000 in Bangladesh: from speculation to reality and exercises. Dengue Bull 25
Zahirul Islam M, Rutherford S, Phung D, Uzzaman MdN, Baum S, Huda MM, Asaduzzaman M, Talukder MRR, Chu C (2018) Correlates of climate variability and dengue fever in two metropolitan cities in Bangladesh. Cureus. https://doi.org/10.7759/cureus.3398
Zan M (2015) Evaluation of land cover and prevalence of dengue in Malaysia
Zeng Q, Yu X, Ni H, Xiao L, Xu T, Wu H, Chen Y, Deng H, Zhang Y, Pei S, Xiao J, Guo P (2023) Dengue transmission dynamics prediction by combining metapopulation networks and Kalman filter algorithm. PLoS Negl Trop Dis 17(6):e0011418. https://doi.org/10.1371/journal.pntd.0011418
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The authors would like to acknowledge the support of department of Urban and Regional Planning of Jahangirnagar University, Bangladesh.
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SR and AB planned the research, completed the data analysis, and wrote the article. MMR conducted the study and contributed to the manuscript's writing. MMR and MTAS reviewed the article and gave important suggestions. SA provided field support and contributed with the survey. MMR contributed to the data and results analysis. The final text was reviewed and approved by all writers.
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Roy, S., Biswas, A., Shawon, M.T.A. et al. Land use and meteorological influences on dengue transmission dynamics in Dhaka city, Bangladesh. Bull Natl Res Cent 48, 32 (2024). https://doi.org/10.1186/s42269-024-01188-0
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DOI: https://doi.org/10.1186/s42269-024-01188-0