Effect of El Niño-Southern Oscillation and local weather on Aedes dvector activity from 2010 to 2018 in Kalutara district, Sri Lanka: a two-stage hierarchical analysis

Effects of the El Niño-Southern Oscillation and seasonal weather conditions on Aedes aegypti infestation in the State of São Paulo (Brazil): A Bayesian spatio-temporal study

BACKGROUND

Seasonal fluctuations in weather are recognized as factors that affect both Aedes (Ae.) aegypti mosquitoes and the diseases they carry, such as dengue fever. The El Niño-Southern Oscillation (ENSO) is widely regarded as one of the most impactful atmospheric phenomena on Earth, characterized by the interplay of shifting ocean temperatures, trade wind intensity, and atmospheric pressure, resulting in extensive alterations in climate conditions. In this study, we investigate the influence of ENSO and local weather conditions on the spatio-temporal variability of Ae. aegypti infestation index.

METHODS

We collected seasonal entomological survey data of immature forms of Ae. aegypti mosquitoes (Breteau index), as well as data on temperature, rainfall and the Oceanic Niño Index (ONI) for the period 2008-2018 over the 645 municipalities of the subtropical State of São Paulo (Brazil). We grounded our analytical approach on a Bayesian framework and we used a hierarchical spatio-temporal model to study the relationship between ENSO tracked by ONI, seasonal weather fluctuations and the larval index, while adjusting for population density and wealth inequalities.

RESULTS

Our results showed a relevant positive effect for El Niño on the Ae. aegypti larval index. In particular, we found that the number of positive containers would be expected to increase by 1.30-unit (95% Credible Intervals (CI): 1.23 to 1.37) with El Niño events (i.e., ≥ 1°C, moderate to strong) respect to neutral (and weak) events. We also found that seasonal rainfall exceeding 153.12 mm appears to have a notable impact on vector index, leading potentially to the accumulation of ample water in outdoor discarded receptacles, supporting the aquatic phase of mosquito development. Additionally, seasonal temperature above 23.30°C was found positively associated to the larval index. Although the State of São Paulo as a whole has characteristics favourable to proliferation of the vector, there were specific areas with a greater tendency for mosquito infestation, since the most vulnerable areas are predominantly situated in the central and northern regions of the state, with hot spots of abundance in the south, especially during El Niño events. Our findings also indicate that social disparities present in the municipalities contributes to Ae. aegypti proliferation.

CONCLUSIONS

Considering the anticipated rise in both the frequency and intensity of El Niño events in the forthcoming decades as a consequence of climate change, the urgency to enhance our ability to track and diminish arbovirus outbreaks is crucial.

The global incidence and trends of three common flavivirus infections (Dengue, yellow fever, and Zika) from 2011 to 2021

Background

Flavivirus pose a continued threat to global health, yet their worldwide burden and trends remain poorly quantified. We aimed to evaluate the global, regional, and national incidence of three common flavivirus infections (Dengue, yellow fever, and Zika) from 2011 to 2021.

Methods

Data on the number and rate of incidence for the three common flavivirus infection in 204 countries and territories were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021. The estimated annual percent change (EAPC) was calculated to quantify the temporal trend during 2011-2016, 2016-2019, and 2019-2021, respectively.

Results

In 2021, an estimated 59,220,428 individuals were infected globally, comprising 58,964,185 cases of dengue, 86,509 cases of yellow fever, and 169,734 cases of Zika virus infection. The age-standardized incidence rate (ASIR) of the three common flavivirus infections increased by an annual average of 5.08% (95% CI 4.12 to 6.05) globally from 2011 to 2016, whereas decreased by an annual average of -8.37% (95% CI -12.46 to -4.08) per year between 2016 to 2019. The ASIR remained stable during 2019-2021, with an average change of 0.69% (95% CI -0.96 to 2.37) per year globally for the three common flavivirus infections. Regionally, the burden of the three common flavivirus infections was primarily concentrated in those regions with middle income, such as South Asia, Southeast Asia, and Tropical Latin America. Additionally, at the country level, there was an inverted "U" relationship between the SDI level and the ASI. Notably, an increase in the average age of infected cases has been observed worldwide, particularly in higher-income regions.

Conclusion

Flavivirus infections are an expanding public health concern worldwide, with considerable regional and demographic variation in the incidence. Policymakers and healthcare providers must stay vigilant regarding the impact of COVID-19 and other environmental factors on the risk of flavivirus infection and be prepared for potential future outbreaks.

Serotype-specific clinical features and spatial distribution of dengue in northern Kerala, India

Background

Collection and compilation of spatial, meteorological, entomological, and virological data are critical in mitigating climate-sensitive emerging infections like dengue. This study was a holistic attempt to understand the dengue situation in the Kasaragod district of Kerala, India.

Methods

This cross-sectional study was conducted in 13 health institutions from June to July 2021. Adult patients presenting with fever and testing positive for NS1 ELISA were subjected to Dengue RT-PCR and serotyping. The spatial and clinical features of the RT-PCR-positive patients, the district's meteorological data, and the vector indices were studied.

Results

The pre-epidemic months were marked by intermittent rainfall, peak ambient temperature and high larval indices. Among the 136 dengue RT-PCR patients studied, 41.2% had DENV2 followed by DENV1 (22.8%), DENV3 (5.9%) and DENV4 (4.4%); with 25% mixed infections. DENV1 showed a higher risk of gastrointestinal manifestations (80.6%, p=0.019) and musculoskeletal symptoms (77.4%, p=0.026) compared with other serotypes.

Conclusions

In the context of dengue hyperendemicity, the possibility of an emerging serotype's dominance coupled with the mixing up of strains should warn the health system regarding future outbreaks. Furthermore, the study emphasizes the importance of monitoring larval indices and the window of opportunity to intervene between environmental predictors and dengue outbreaks.

Current and lagged associations of meteorological variables and Aedes mosquito indices with dengue incidence in the Philippines

BACKGROUND

Dengue is an increasing health burden that has spread throughout the tropics and sub-tropics. There is currently no effective vaccine and control is only possible through integrated vector management. Early warning systems (EWS) to alert potential dengue outbreaks are currently being explored but despite showing promise are yet to come to fruition. This study addresses the association of meteorological variables with both mosquito indices and dengue incidences and assesses the added value of additionally using mosquito indices for predicting dengue incidences.

METHODOLOGY/PRINCIPAL FINDINGS

Entomological surveys were carried out monthly for 14 months in six sites spread across three environmentally different cities of the Philippines. Meteorological and dengue data were acquired. Non-linear generalized additive models were fitted to test associations of the meteorological variables with both mosquito indices and dengue cases. Rain and the diurnal temperature range (DTR) contributed most to explaining the variation in both mosquito indices and number of dengue cases. DTR and minimum temperature also explained variation in dengue cases occurring one and two months later and may offer potentially useful variables for an EWS. The number of adult mosquitoes did associate with the number of dengue cases, but contributed no additional value to meteorological variables for explaining variation in dengue cases.

CONCLUSIONS/SIGNIFICANCE

The use of meteorological variables to predict future risk of dengue holds promise. The lack of added value of using mosquito indices confirms several previous studies and given the onerous nature of obtaining such information, more effort should be placed on improving meteorological information at a finer scale to evaluate efficacy in early warning of dengue outbreaks.

Long-term effects of climate factors on dengue fever over a 40-year period

BACKGROUND

Dengue fever stands as one of the most extensively disseminated mosquito-borne infectious diseases worldwide. While numerous studies have investigated its influencing factors, a gap remains in long-term analysis, impeding the identification of temporal patterns, periodicity in transmission, and the development of effective prevention and control strategies. Thus, we aim to analyze the periodicity of dengue fever incidence and explore the association between various climate factors and the disease over an extended time series.

METHODS

By utilizing monthly dengue fever cases and climate data spanning four decades (1978-2018) in Guangdong province, China, we employed wavelet analysis to detect dengue fever periodicity and analyze the time-lag relationship with climate factors. Additionally, Geodetector q statistic was employed to quantify the explanatory power of each climate factor and assess interaction effects.

RESULTS

Our findings revealed a prolonged transmission period of dengue fever over the 40-year period, transitioning from August to November in the 1970s to nearly year-round in the 2010s. Moreover, we observed lags of 1.5, 3.5, and 3 months between dengue fever and temperature, relative humidity, and precipitation, respectively. The explanatory power of precipitation, temperature, relative humidity, and the Oceanic Niño Index (ONI) on dengue fever was determined to be 18.19%, 12.04%, 11.37%, and 5.17%, respectively. Dengue fever exhibited susceptibility to various climate factors, with notable nonlinear enhancement arising from the interaction of any two variables. Notably, the interaction between precipitation and humidity yielded the most significant effect, accounting for an explanatory power of 75.32%.

CONCLUSIONS

Consequently, future prevention and control strategies for dengue fever should take into account these climate changes and formulate corresponding measures accordingly. In regions experiencing the onset of high temperatures, humidity, and precipitation, it is imperative to initiate mosquito prevention and control measures within a specific window period of 1.5 months.

Indian Ocean temperature anomalies predict long-term global dengue trends

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

Permethrin Contamination of Sawgrass Marshes and Potential Risk for the Imperiled Klot's Skipper Butterfly (Euphyes pilatka klotsi)

Nontarget effects from mosquito control operations are possible in habitats adjacent to areas targeted by ultra-low-volume (ULV) sprays of permethrin for adult mosquito control. We assessed the risks of permethrin exposure to butterflies, particularly the imperiled Klot's skipper, when exposed to ground-based ULV sprays. Samples of larval host plant leaves (sawgrass) were collected in June (in mosquito season) and January (outside mosquito season) of 2015 from sawgrass marsh habitats of the National Key Deer Wildlife Refuge (Big Pine Key, FL, USA) and analyzed for permethrin. Permethrin detection was higher in June (detected on 70% of samples) than in January (30%), and concentrations were significantly higher in June (geomean = 2.1 ng/g, median = 2.4) relative to January (0.4 ng/g, median = 0.2). Dietary risk for 4th to 5th-instar larvae was low based on the measured residues. The AGricultural DISPersal model (Ver. 8.26) was used to estimate permethrin residues on sawgrass following ULV sprays (deposited residues) to estimate immediate postspray risk. Estimated deposited residues (33-543 ng/g) were much higher than measured residues, which leads to a higher risk likelihood for butterfly larvae immediately after ULV sprays. The difference between estimated and measured residues, and between the two risk estimations, reflects uncertainty in risk estimates based on the measured residues. Research on modeling deposited pesticide residues following ground-based ULV spray is limited. More research on estimating deposited pesticide residues from truck-mounted ULV sprayers could help reduce uncertainty in the risk predictions for nontarget insects like butterflies. Environ Toxicol Chem 2024;43:267-278. Published 2023. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Nonlinear and Multidelayed Effects of Meteorological Drivers on Human Respiratory Syncytial Virus Infection in Japan

In this study, we aimed to characterize the nonlinear and multidelayed effects of multiple meteorological drivers on human respiratory syncytial virus (HRSV) infection epidemics in Japan. The prefecture-specific weekly time-series of the number of newly confirmed HRSV infection cases and multiple meteorological variables were collected for 47 Japanese prefectures from 1 January 2014 to 31 December 2019. We combined standard time-series generalized linear models with distributed lag nonlinear models to determine the exposure-lag-response association between the incidence relative risks (IRRs) of HRSV infection and its meteorological drivers. Pooling the 2-week cumulative estimates showed that overall high ambient temperatures (22.7 °C at the 75th percentile compared to 16.3 °C) and high relative humidity (76.4% at the 75th percentile compared to 70.4%) were associated with higher HRSV infection incidence (IRR for ambient temperature 1.068, 95% confidence interval [CI], 1.056-1.079; IRR for relative humidity 1.045, 95% CI, 1.032-1.059). Precipitation revealed a positive association trend, and for wind speed, clear evidence of a negative association was found. Our findings provide a basic picture of the seasonality of HRSV transmission and its nonlinear association with multiple meteorological drivers in the pre-HRSV-vaccination and pre-coronavirus disease 2019 (COVID-19) era in Japan.

El Niño Southern Oscillation (ENSO) effects on local weather, arboviral diseases, and dynamics of managed and unmanaged populations of Aedes aegypti (Diptera: Culicidae) in Puerto Rico

We investigated the effects of interannual El Niño Southern Oscillation (ENSO) events on local weather, Aedes aegypti populations, and combined cases of dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV) viruses in 2 communities with mass mosquito trapping and 2 communities without mosquito control in southern Puerto Rico (2013-2019). Gravid adult Ae. aegypti populations were monitored weekly using Autocidal Gravid Ovitraps (AGO traps). Managing Ae. aegypti populations was done using 3 AGO traps per home in most homes. There were drought conditions in 2014-2015 concurrent with the emergence of a strong El Niño (2014-2016), wetter conditions during La Niña (2016-2018), a major hurricane (2017), and a weaker El Niño (2018-2019). The main factor explaining differences in Ae. aegypti abundance across sites was mass trapping. Populations of Ae. aegypti reached maximum seasonal values during the wetter and warmer months of the year when arbovirus epidemics occurred. El Niño was significantly associated with severe droughts that did not impact the populations of Ae. aegypti. Arbovirus cases at the municipality level were positively correlated with lagged values (5-12 mo.) of the Oceanic El Niño Index (ONI), droughts, and abundance of Ae. aegypti. The onset of strong El Niño conditions in Puerto Rico may be useful as an early warning signal for arboviral epidemics in areas where the abundance of Ae. aegypti exceeds the mosquito density threshold value.

Assessing the associations between Aedes larval indices and dengue risk in Kalutara district, Sri Lanka: a hierarchical time series analysis from 2010 to 2019

BACKGROUND

Dengue is a major public health problem in Sri Lanka. Aedes vector surveillance and monitoring of larval indices are routine, long-established public health practices in the country. However, the association between Aedes larval indices and dengue incidence is poorly understood. It is crucial to evaluate lagged effects and threshold values of Aedes larval indices to set pragmatic targets for sustainable vector control interventions.

METHODS

Monthly Aedes larval indices and dengue cases in all 10 Medical Officer of Health (MOH) divisions in Kalutara district were obtained from 2010 to 2019. Using a novel statistical approach, a distributed lag non-linear model and a two-staged hierarchical meta-analysis, we estimated the overall non-linear and delayed effects of the Premise Index (PI), Breteau Index (BI) and Container Index (CI) on dengue incidence in Kalutara district. A set of MOH division-specific variables were evaluated within the same meta-analytical framework to determine their moderator effects on dengue risk. Using generalized additive models, we assessed the utility of Aedes larval indices in predicting dengue incidence.

RESULTS

We found that all three larval indices were associated with dengue risk at a lag of 1 to 2 months. The relationship between PI and dengue was homogeneous across MOH divisions, whereas that with BI and CI was heterogeneous. The threshold values of BI, PI and CI associated with dengue risk were 2, 15 and 45, respectively. All three indices showed a low to moderate accuracy in predicting dengue risk in Kalutara district.

CONCLUSIONS

This study showed the potential of vector surveillance information in Kalutara district in developing a threshold-based, location-specific early warning system with a lead time of 2 months. The estimated thresholds are nonetheless time-bound and may not be universally applicable. Whenever longitudinal vector surveillance data areavailable, the methodological framework we propose here can be used to estimate location-specific Aedes larval index thresholds in any other dengue-endemic setting.