| Literature DB >> 34499653 |
Antonios Kolimenakis1, Sabine Heinz2, Michael Lowery Wilson2, Volker Winkler2, Laith Yakob3, Antonios Michaelakis1, Dimitrios Papachristos1, Clive Richardson4, Olaf Horstick2.
Abstract
BACKGROUND: This systematic review aims to assess how different urbanisation patterns related to rapid urban growth, unplanned expansion, and human population density affect the establishment and distribution of Aedes aegypti and Aedes albopictus and create favourable conditions for the spread of dengue, chikungunya, and Zika viruses. METHODS ANDEntities:
Mesh:
Year: 2021 PMID: 34499653 PMCID: PMC8428665 DOI: 10.1371/journal.pntd.0009631
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Evidence table.
| Author year | Study location and population density | Study type | Vector | Disease | Urbanisation variable | Measured outcome | Key findings and conclusions | Influence factor | Quality assessment score |
|---|---|---|---|---|---|---|---|---|---|
| Estallo and colleagues (2018) [ | Argentina, Cordoba; 2,273 | Ecological model |
| Dengue, chikungunya, and Zika | Urban construction | Environmental, socioeconomic, and demographic factors driving the distribution of | The | 40 | |
| Fuentes-Vallejo and colleagues (2015) [ | Colombia, Arauca; 4,321–9,332 | Ecological model | Dengue | Artificial geographic space | Relationship between the territory’s structures and dynamics and vector density | The study found a relationship between territorial structures and dynamics and vector density in both study areas, where the interaction between ecological and social systems shape areas with high and low | 100 | ||
| Satoto and colleagues (2019) [ | Indonesia, Magelang; 6,693 | Entomological and epidemiological surveillance | Dengue | Human population density and urban growth | Association between insecticide resistance and DHF case distribution related to human urbanisation | Study showed increasing population size and human urbanisation from less urban areas to urban areas in almost the same period as the occurrence of insecticide resistance, potentially related to slight increase in population size and human urbanisation | 80 | ||
| Zahouli and colleagues (2016) [ | Côte d’Ivoire, Treichville; 1,800 | Entomological surveillance | Dengue and yellow fever | Human population density | Assess | Urbanisation correlated with a substantially higher abundance in | 100 | ||
| Li and colleagues (2014) [ | China, Guangzhou; 3,000 | Entomological surveillance |
| Dengue | Human population density and urban growth | Determine how environmental changes due to urbanisation affect the ecology of | Urbanisation substantially increased the density, larval development rate, and adult survival time of | 100 | |
| Zahouli and colleagues (2017) [ | Côte d’Ivoire, Treichville; 1,800 | Entomological surveillance | Dengue and yellow fever | Human population density and urban growth | Larval ecology of | In Côte d’Ivoire, urbanisation is associated with high abundance of | 100 | ||
| Cox and colleagues (2007) [ | Puerto Rico, San Juan; 3,187 | Entomological surveillance | Dengue | Urban construction | Investigate habitat distribution of adult | 100 | |||
| Manica and colleagues (2016) [ | Italy, Rome; 6,000 | Entomological surveillance and ecological model | Dengue and chikungunya | Artificial geographic space and human population density | Ecoclimatic factors affecting | 100 | |||
| Samson and colleagues (2015) [ | Haiti, Cap-Haïtien; 5,129 | Entomological surveillance and ecological model | Dengue and chikungunya | Urban growth | Impact of unplanned urbanisation on mosquito ecology and vector-borne diseases by assessing land use and change patterns | 100 | |||
| Carbajo and colleagues (2006) [ | Argentina, Buenos Aires; 15,000 | Entomological surveillance and spatial model | Dengue and yellow fever | Urban construction and human population density | Oviposition as a function of urbanisation variables | The proportion of weeks infested and the total number of eggs showed spatial continuity and were higher in areas that had higher densities of houses and were closer to industrial sites; the spatial pattern of | 100 | ||
| Ren and colleagues (2019) [ | China, Guangzhou; 18,836 | Spatial model | Dengue | Human population density and urban growth | The relationships between reported DF epidemics during 2012–2017, GDP, the traffic system (road density, bus, and/or subway stations), and urban villages derived from high-resolution remotely sensed imagery in the central area of Guangzhou | Urban villages possessed higher values of DF cases density, incidence rates, and population density in the central region of Guangzhou City; urban villages result in a high environmental suitability for some vectors (e.g., | 100 | ||
| Messina and colleagues (2019) [ | Global | Ecological model | Dengue | Human population density and urban density | Climate, population, and socioeconomic projections for the years 2020, 2050, and 2080 to project future changes in virus suitability and human population at risk | DENV transmission is maintained in urban settings where humans and mosquitoes are the only known hosts, with a sylvatic cycle occurring in nonhuman primates in forested areas and rarely resulting in transmission to humans | 100 | ||
| Piedrahita and colleagues (2018) [ | Colombia, Medellin; 6,925 | Epidemiological surveillance and spatial analysis | Dengue | Human population density | Impact of population density and entomological indexes associated with the spatial distribution of DENV seroprevalence | Population density and | 60 | ||
| Padmanabha and colleagues (2012) [ | Colombia, Armenia; 2,100 | Spatial model | Dengue | Human population density | Evaluate the combined impacts of variation in | Increased human density favoured Dengue R0, and when the likelihood of human introduction of virus was incorporated into risk, a strong interaction arose between vector production and human density | 80 | ||
| Disease transmission | |||||||||
| Freitas and colleagues (2019) [ | Brazil, Rio De Janeiro; 5,249 | Ecological | Dengue, chikungunya, and Zika | Human population density and artificial geographic space | Detect spatiotemporal clustering for each disease separately and for all 3 simultaneously | Simultaneous clusters of the 3 diseases were more likely in neighbourhoods with a combination of high population density and low socioeconomic status | Disease transmission | 80 | |
| Delmelle and colleagues (2016) [ | Colombia, Cali; 4,000 | Ecological model | Dengue | Human population density | The dynamics of DF transmission relevant to changes in environmental conditions, as well as local demographic and socioeconomic factors | Among the strongest predicting variables for DF were population density and socioeconomic stratum | Disease transmission | 100 | |
| Bouzid and colleagues (2014) [ | Europe and Mexico | Ecological model | Dengue | Human population density | Dengue risk in Europe under climate change scenarios; DF risk in Europe in terms of disease occurrence rather than mosquito presence | Population and urbanisation projections for Europe show that minor changes are expected (with some local variation), especially when compared to other parts of the world (where significant increase in population size and urbanisation are expected until 2100); climate change is likely to contribute to increased dengue risk (and possibly other mosquito-borne diseases) in many parts of Europe, especially towards the end of the century | Disease transmission | 100 | |
| Cao and colleagues (2017) [ | China, Guangzhou; 17,562 | Ecological model | Dengue | Human population density and urban construction | Investigate the independent and interactive effects of several socioecological factors on the 2014 dengue epidemic at a township/street level in Guangzhou | Socioecological factors including road density, temperature, urbanisation level, and urban village, might either separately or jointly influence the spatial distribution of DF in Guangzhou | Disease transmission | 100 | |
| Akhtar and colleagues (2016) [ | India, Delhi, 11,312 | Ecological model | Dengue | Urban growth and urban density | Link of dengue prevalence with the heat entrapped by the urban structure accentuating the temperature and humidity, thus helping | Correlation was found of urban density to total cases and urban population to total cases; seasonal or cyclic factors of the disease are combined with the fluctuating humidity and temperature data and the urban density (a proxy variable of urban growth) that creates heat effect in some of the dense area and thus leads to pocketed outbreak of the disease | Disease transmission | 40 | |
| Teixeira and colleagues (2007) [ | Brazil, Salvador; 1,834–49,980 | Epidemiological surveillance | Dengue | Human population density | Relationship between the intensity of virus circulation and the population’s living conditions or between group immunity and | The risk of infection was high in almost all the areas, including in the areas with good living conditions. It is likely that these dynamics is at least partially due to the fact that in Salvador, high population density is found both in areas with precarious living conditions and in those where economically more favoured populations live | Disease transmission | 100 | |
| Qi and colleagues (2015) [ | China, Pearl River Delta; 8,687 | Epidemiological surveillance and ecological model | Dengue | Human population density and urban growth | Assess core contributors to the occurrence of DF from the perspective of the social economy and the environment | DF transmission has been reported in both rural and urban areas. However, urban environments are characterised by many factors, such as a higher population, poor hygiene, poor housing conditions, and less environmental management; rapid urbanisation with large populations living in peri-urban slums provides attractive features for the | Disease transmission | 100 | |
| Barrera and colleagues (2000) [ | Venezuela, Maracay; 1,439 | Epidemiological surveillance and spatial analysis | Dengue | Human population density | Relation of dengue with the number of inhabitants and population density, during the 1993–1998 period, leading to 10,576 reported cases of dengue, 2,593 cases of DHF and 8 deaths | The incidence of DHF was significantly related to the incidence of dengue, the number of inhabitants in an area, and population density | Disease transmission | 100 | |
| Vallée and colleagues (2009) [ | Laos, Vientiane; 3,255 | Epidemiological surveillance and spatial analysis | Dengue | Human population density and urban construction | Explore the link between flavivirus seroprevalence and urbanisation levels of residential neighbourhoods | Level of urbanisation and length of residence were the 2 most significant factors in predicting individual risk of flavivirus infection; significant association between flavivirus seroprevalence and urbanisation was found within Vientiane City | Disease transmission | 100 | |
| Wu and colleagues (2009) [ | Taiwan; 7,100 | Epidemiological surveillance and spatial analysis | Dengue | Human population density | Role of urbanisation and temperature increase in spatial patterns of dengue | Higher level of urbanisation was also associated with increasing risk on the occurrence of DF at township level; changing temperature pattern and urbanisation as most important determinants predicting DF occurrence in Taiwan | Disease transmission | 100 | |
| Lin and colleagues (2011) [ | Taiwan; 7,100 | Epidemiological surveillance and spatial model | Dengue | Human population density | Local spatial variations of dengue–mosquito and dengue–human relationships within a study area | Higher human densities were shown to contribute to higher dengue incidence rates; in some areas, higher dengue incidences were associated with higher vector/host densities, but in some areas, higher incidences were related to lower vector/host densities | Disease transmission | 80 | |
| Struchiner and colleagues (2015) [ | Singapore; 7,804 | Predictive model | Dengue | Human population density | Contributions of putative drivers for the rise of dengue in Singapore: population growth, climate parameters, and international air passenger arrivals from dengue endemic countries, for the time period of 1974 until 2011 | Population growth was the leading independent factor associated with the increase in dengue cases observed in Singapore over the past 40 years, followed by mean temperature change | Disease transmission | 100 | |
| Zheng and colleagues (2019) [ | China, Pearl River Delta; 6,000 | Spatial model | Dengue | Human population density and urban density | Spatiotemporal patterns and potential influencing factors of DF epidemics | Population density and urban land ratio were the socioeconomic factors explaining the largest variance in regional epidemics in terms of spatial distribution | Disease transmission | 100 | |
| Yue and colleagues (2018) [ | China, Guangdong; 1,928 | Spatial model | Dengue | Human population density | Environmental and socioeconomic risk factors leading to DF | DF was positively correlated with population density and GDP in study areas; water and a suitable temperature are also essential factors for the larvae of the DENV vector, the | Disease transmission | 100 | |
| Khalid and colleagues (2015) [ | Pakistan, Rawalpindi: 8,100; Islamabad: 2,089; Lahore: 6,300; Karachi: 3,900 | Spatial model | Dengue | Urban growth, urban density, and human population density | How change in urbanisation and population density and meteorological parameters affect dengue transmission | Increased urbanisation and population density has supported the dengue transmission in the mega cities of Pakistan. The anthropogenic activities have the great influence on the dengue transmission, survival, and growth as it require the urban environments. | Disease transmission | 80 | |
DENV, dengue virus; DF, dengue fever; DHF, dengue hemorrhagic fever; GDP, gross domestic product.
Fig 1PRISMA flow diagram.
IRIS, Institutional Repository for Information Sharing; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; VHL, Virtual Health Library; WHOLIS, WHO Library Database.