Extended-Spectrum ß-Lactamase-Producing Escherichia coli and Klebsiella pneumoniae: Risk Factors and Economic Burden Among Patients with Bloodstream Infections.

Introduction: Although Extended-spectrum ß-lactamase-producing Escherichia coli and Klebsiella pneumoniae (ESBL-EK) significantly contribute to bloodstream infections, their economic repercussions remain largely unquantified. Data Source and Methods: We performed a retrospective analysis of inpatients diagnosed with Escherichia coli or Klebsiella pneumoniae bacteremia in a tertiary hospital from January 2020 to December 2022 in Guangzhou, China. We employed the chi-square test to examine ESBL risk factors and utilized propensity score matching (PSM) to negate baseline confounding factors, assessing economic burden through disability-adjusted life years (DALYs), hospital costs and productivity losses. We employed mediation analysis to eliminate confounding factors and better identify ESBL sources of burden related. Results: We found 166 ESBL-EC/KP BSI patients (52.2% of the total examined 318 patients). Post-PSM analysis revealed that ESBL-producing EC/KP will reduce the effectiveness of empirical medication by 19.8%, extend the total length of hospitalization by an average of 3 days, and increase the patient's financial burden by US$2047. No significant disparity was found in overall mortality and mean DALYs between the groups. Mediation analysis showed that the link between ESBL and hospital costs is predominantly, if not entirely, influenced by the appropriateness of empirical antibiotic treatment and length of hospital stay. Conclusion: Patients with BSI due to ESBL-producing ESBL-EK incur higher costs compared to those with non-ESBL-EK BSI. This cost disparity is rooted in varying rates of effective empirical antimicrobial therapy and differences in hospital stay durations. A nuanced approach, incorporating a thorough understanding of regional epidemiological trends and judicious antibiotic use, is crucial for mitigating the financial impact on patients.

Costs-effectiveness and cost components of pharmaceutical and non-pharmaceutical interventions affecting antibiotic resistance outcomes in hospital patients: a systematic literature review.

INTRODUCTION: Limited information on costs and the cost-effectiveness of hospital interventions to reduce antibiotic resistance (ABR) hinder efficient resource allocation. METHODS: We conducted a systematic literature review for studies evaluating the costs and cost-effectiveness of pharmaceutical and non-pharmaceutical interventions aimed at reducing, monitoring and controlling ABR in patients. Articles published until 12 December 2023 were explored using EconLit, EMBASE and PubMed. We focused on critical or high-priority bacteria, as defined by the WHO, and intervention costs and incremental cost-effectiveness ratio (ICER). Following Preferred Reporting Items for Systematic review and Meta-Analysis guidelines, we extracted unit costs, ICERs and essential study information including country, intervention, bacteria-drug combination, discount rates, type of model and outcomes. Costs were reported in 2022 US dollars ($), adopting the healthcare system perspective. Country willingness-to-pay (WTP) thresholds from Woods et al 2016 guided cost-effectiveness assessments. We assessed the studies reporting checklist using Drummond's method. RESULTS: Among 20 958 articles, 59 (32 pharmaceutical and 27 non-pharmaceutical interventions) met the inclusion criteria. Non-pharmaceutical interventions, such as hygiene measures, had unit costs as low as $1 per patient, contrasting with generally higher pharmaceutical intervention costs. Several studies found that linezolid-based treatments for methicillin-resistant Staphylococcus aureus were cost-effective compared with vancomycin (ICER up to $21 488 per treatment success, all 16 studies' ICERs

The impact of inpatient bloodstream infections caused by antibiotic-resistant bacteria in low- and middle-income countries: A systematic review and meta-analysis.

BACKGROUND: Bloodstream infections (BSIs) produced by antibiotic-resistant bacteria (ARB) cause a substantial disease burden worldwide. However, most estimates come from high-income settings and thus are not globally representative. This study quantifies the excess mortality, length of hospital stay (LOS), intensive care unit (ICU) admission, and economic costs associated with ARB BSIs, compared to antibiotic-sensitive bacteria (ASB), among adult inpatients in low- and middle-income countries (LMICs). METHODS AND FINDINGS: We conducted a systematic review by searching 4 medical databases (PubMed, SCIELO, Scopus, and WHO's Global Index Medicus; initial search n = 13,012 from their inception to August 1, 2022). We only included quantitative studies. Our final sample consisted of n = 109 articles, excluding studies from high-income countries, without our outcomes of interest, or without a clear source of bloodstream infection. Crude mortality, ICU admission, and LOS were meta-analysed using the inverse variance heterogeneity model for the general and subgroup analyses including bacterial Gram type, family, and resistance type. For economic costs, direct medical costs per bed-day were sourced from WHO-CHOICE. Mortality costs were estimated based on productivity loss from years of potential life lost due to premature mortality. All costs were in 2020 USD. We assessed studies' quality and risk of publication bias using the MASTER framework. Multivariable meta-regressions were employed for the mortality and ICU admission outcomes only. Most included studies showed a significant increase in crude mortality (odds ratio (OR) 1.58, 95% CI [1.35 to 1.80], p < 0.001), total LOS (standardised mean difference "SMD" 0.49, 95% CI [0.20 to 0.78], p < 0.001), and ICU admission (OR 1.96, 95% CI [1.56 to 2.47], p < 0.001) for ARB versus ASB BSIs. Studies analysing Enterobacteriaceae, Acinetobacter baumanii, and Staphylococcus aureus in upper-middle-income countries from the African and Western Pacific regions showed the highest excess mortality, LOS, and ICU admission for ARB versus ASB BSIs per patient. Multivariable meta-regressions indicated that patients with resistant Acinetobacter baumanii BSIs had higher mortality odds when comparing ARB versus ASB BSI patients (OR 1.67, 95% CI [1.18 to 2.36], p 0.004). Excess direct medical costs were estimated at $12,442 (95% CI [$6,693 to $18,191]) for ARB versus ASB BSI per patient, with an average cost of $41,103 (95% CI [$30,931 to $51,274]) due to premature mortality. Limitations included the poor quality of some of the reviewed studies regarding the high risk of selective sampling or failure to adequately account for relevant confounders. CONCLUSIONS: We provide an overview of the impact ARB BSIs in limited resource settings derived from the existing literature. Drug resistance was associated with a substantial disease and economic burden in LMICs. Although, our results show wide heterogeneity between WHO regions, income groups, and pathogen-drug combinations. Overall, there is a paucity of BSI data from LMICs, which hinders implementation of country-specific policies and tracking of health progress.

Global antimicrobial-resistance drivers: an ecological country-level study at the human-animal interface.

BACKGROUND: Antimicrobial resistance (AMR) is a pressing, holistic, and multisectoral challenge facing contemporary global health. In this study we assessed the associations between socioeconomic, anthropogenic, and environmental indicators and country-level rates of AMR in humans and food-producing animals. METHODS: In this modelling study, we obtained data on Carbapenem-resistant Acinetobacter baumanii and Pseudomonas aeruginosa, third generation cephalosporins-resistant Escherichia coli and Klebsiella pneumoniae, oxacillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecium AMR in humans and food-producing animals from publicly available sources, including WHO, World Bank, and Center for Disease Dynamics Economics and Policy. AMR in food-producing animals presented a combined prevalence of AMR exposure in cattle, pigs, and chickens. We used multivariable ß regression models to determine the adjusted association between human and food-producing animal AMR rates and an array of ecological country-level indicators. Human AMR rates were classified according to the WHO priority pathogens list and antibiotic-bacterium pairs. FINDINGS: Significant associations were identified between animal antimicrobial consumption and AMR in food-producing animals (OR 1·05 [95% CI 1·01-1·10]; p=0·013), and between human antimicrobial consumption and AMR specifically in WHO critical priority (1·06 [1·00-1·12]; p=0·035) and high priority (1·22 [1·09-1·37]; p<0·0001) pathogens. Bidirectional associations were also found: animal antibiotic consumption was positively linked with resistance in critical priority human pathogens (1·07 [1·01-1·13]; p=0·020) and human antibiotic consumption was positively linked with animal AMR (1·05 [1·01-1·09]; p=0·010). Carbapenem-resistant Acinetobacter baumanii, third generation cephalosporins-resistant Escherichia coli, and oxacillin-resistant Staphylococcus aureus all had significant associations with animal antibiotic consumption. Analyses also suggested significant roles of socioeconomics, including governance on AMR rates in humans and animals. INTERPRETATION: Reduced rates of antibiotic consumption alone will not be sufficient to combat the rising worldwide prevalence of AMR. Control methods should focus on poverty reduction and aim to prevent AMR transmission across different One Health domains while accounting for domain-specific risk factors. The levelling up of livestock surveillance systems to better match those reporting on human AMR, and, strengthening all surveillance efforts, particularly in low-income and middle-income countries, are pressing priorities. FUNDING: None.

Japanese Encephalitis Emergence in Australia: The Potential Population at Risk.

In Australia, Japanese encephalitis virus circulated in tropical north Queensland between 1995 and 2005. In 2022, a dramatic range expansion across the southern states has resulted in 30 confirmed human cases and 6 deaths. We discuss the outbreak drivers and estimate the potential size of the human population at risk.

Knowledge, Attitudes and Perception of Mosquito Control in Different Citizenship Regimes within and Surrounding the Malakasa Open Accommodation Refugee Camp in Athens, Greece.

The study aims to evaluate the Knowledge, Attitude and Perception (KAP) of different societal groups concerning the implementation of targeted community-based mosquito surveillance and control interventions in different citizenship regimes. Targeted surveys were carried out within Malakasa camp for migrants and refugees, neighboring residential areas and urban areas in the wider Athens metropolitan area to investigate different knowledge levels and the role that both local and migrant communities can play in the implementation of community-based interventions based on their attitudes and perceptions. A scoring system was used to rate the collected responses. Results indicate different levels of KAP among the various groups of respondents and different priorities that should be considered in the design and execution of community interventions. Findings indicate a lower level of Knowledge Attitudes and Perceptions for the migrants, while the rate of correct answers for Perception significantly improved for migrants following a small-scale information session. The study highlights disparities in the levels of knowledge for certain public health issues and the feasibility of certain approaches for alleviating health-related challenges such as mosquito-borne diseases. Findings suggest that essential preparedness is needed by public authorities to respond to public health challenges related to migration and the spread of vector-borne diseases.

Predictable Chikungunya Infection Dynamics in Brazil.

Chikungunya virus (CHIKV) was first imported into the Caribbean in 2013 and subsequently spread across the Americas. It has infected millions in the region and Brazil has become the hub of ongoing transmission. Using Seasonal Autoregressive Integrated Moving Average (SARIMA) models trained and validated on Brazilian data from the Ministry of Health's notifiable diseases information system, we tested the hypothesis that transmission in Brazil had transitioned from sporadic and explosive to become more predictable. Consistency weighted, population standardized kernel density estimates were used to identify municipalities with the most consistent inter-annual transmission rates. Spatial clustering was assessed per calendar month for 2017−2021 inclusive using Moran's I. SARIMA models were validated on 2020−2021 data and forecasted 106,162 (95%CI 27,303−200,917) serologically confirmed cases and 339,907 (95%CI 35,780−1035,449) total notifications for 2022−2023 inclusive, with >90% of cases in the Northeast and Southeast regions. Comparing forecasts for the first five months of 2022 to the most up-to-date ECDC report (published 2 June 2022) showed remarkable accuracy: the models predicted 92,739 (95%CI 20,685−195,191) case notifications during which the ECDC reported 92,349 case notifications. Hotspots of consistent transmission were identified in the states of Para and Tocantins (North region); Rio Grande do Norte, Paraiba and Pernambuco (Northeast region); and Rio de Janeiro and eastern Minas Gerais (Southeast region). Significant spatial clustering peaked during late summer/early autumn. This analysis highlights how CHIKV transmission in Brazil has transitioned, making it more predictable and thus enabling improved control targeting and site selection for trialing interventions.

ß-Lactam-Resistant Streptococcus pneumoniae Dynamics Following Treatment: A Dose-Response Meta-analysis.

BACKGROUND: Patient exposure to antibiotics promotes the emergence of drug-resistant pathogens. The aim of this study was to identify whether the temporal dynamics of resistance emergence at the individual-patient level were predictable for specific pathogen-drug classes. METHODS: Following a systematic review, a novel robust error meta-regression method for dose-response meta-analysis was used to estimate the odds ratio (OR) for carrying resistant bacteria during and following treatment compared to baseline. Probability density functions fitted to the resulting dose-response curves were then used to optimize the period during and/or after treatment when resistant pathogens were most likely to be identified. RESULTS: Studies of Streptococcus pneumoniae treatment with ß-lactam antibiotics demonstrated a peak in resistance prevalence among patients 4 days after completing treatment with a 3.32-fold increase in odds (95% confidence interval [CI], 1.71-6.46). Resistance waned more gradually than it emerged, returning to preexposure levels 1 month after treatment (OR, 0.98 [95% CI, .55-1.75]). Patient isolation during the peak dose-response period would be expected to reduce the risk that a transmitted pathogen is resistant equivalently to a 50% longer isolation window timed from the first day of treatment. CONCLUSIONS: Predictable temporal dynamics of resistance levels have implications both for surveillance and control.

Mathematical modelling to assess the feasibility of Wolbachia in malaria vector biocontrol.

Releasing mosquitoes transinfected with the endosymbiotic bacterium Wolbachia is a novel strategy for interrupting vector-borne pathogen transmission. Following its success in controlling arboviruses spread by Aedes aegypti, this technology is being adapted for anopheline malaria vectors. However, antagonistic interactions between Wolbachia and naturally resident Asaia bacteria in malaria vectors have been demonstrated experimentally, potentially jeopardising Wolbachia biocontrol. We developed the first mathematical model accounting for interspecific competition between endosymbionts to assess the feasibility of this novel strategy for controlling malaria. First, Asaia prevalences among natural mosquito populations were compared with simulations parametrized with rates of Asaia transmission reported from laboratory studies. Discrepancies between projections and natural Asaia prevalences indicated potential overestimation of Asaia transmissibility in artificial laboratory settings. With parametrization that matches natural Asaia prevalence, simulations identified redundancies in Asaia's many infection routes (vertical, sexual and environmental). This resilience was only overcome when Wolbachia conferred very high resistance to environmental infection with Asaia, resulting in Wolbachia fixation and Asaia exclusion. Wolbachia's simulated spread was prevented when its maternal transmission was impeded in coinfected mosquitoes and the pre-control Asaia prevalence was beyond a threshold of 60-75%. This theoretical assessment highlights critical next steps in laboratory experiments to inform this strategy's feasibility.

Zika Virus after the Public Health Emergency of International Concern Period, Brazil.

More than 100,000 Zika virus cases have been reported in Brazil since the Public Health Emergency of International Concern period ended in 2016. We analyzed cases in Brazil during 2017-2021 to identify transmission trends and forecast future infection hotspots. Our results can be used for targeted interventions to reduce transmission.

The importance of saturating density dependence for population-level predictions of SARS-CoV-2 resurgence compared with density-independent or linearly density-dependent models, England, 23 March to 31 July 2020.

BackgroundPopulation-level mathematical models of outbreaks typically assume that disease transmission is not impacted by population density ('frequency-dependent') or that it increases linearly with density ('density-dependent').AimWe sought evidence for the role of population density in SARS-CoV-2 transmission.MethodsUsing COVID-19-associated mortality data from England, we fitted multiple functional forms linking density with transmission. We projected forwards beyond lockdown to ascertain the consequences of different functional forms on infection resurgence.ResultsCOVID-19-associated mortality data from England show evidence of increasing with population density until a saturating level, after adjusting for local age distribution, deprivation, proportion of ethnic minority population and proportion of key workers among the working population. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these classical model structures over- and underestimate the delay in infection resurgence following the release of lockdown.ConclusionIdentifying saturation points for given populations and including transmission terms that account for this feature will improve model accuracy and utility for the current and future pandemics.

Domestic risk factors for increased rodent abundance in a Lassa fever endemic region of rural Upper Guinea.

Lassa fever (LF) is a viral haemorrhagic fever endemic in West Africa and spread primarily by the multimammate rat, Mastomys natalensis. As there is no vaccine, reduction of rodent-human transmission is essential for disease control. As the household is thought to be a key site of transmission, understanding domestic risk factors for M. natalensis abundance is crucial. Rodent captures in conjunction with domestic surveys were carried out in 6 villages in an area of rural Upper Guinea with high LF endemicity. 120 rodent traps were set in rooms along a transect in each village for three nights, and the survey was administered in each household on the transects. This study was able to detect several domestic risk factors for increased rodent abundance in rural Upper Guinea. Regression analysis demonstrated that having > 8 holes (RR = 1.8 [1.0004-3.2, p = 0.048), the presence of rodent burrows (RR = 2.3 [1.6-3.23, p = 0.000003), and being in a multi-room square building (RR = 2.0 [1.3-2.9], p = 0.001) were associated with increased rodent abundance. The most addressable of these may be rodent burrows, as burrow patching is a relatively simple process that may reduce rodent entry. Further study is warranted to explicitly link domestic rodent abundance to LF risk, to better characterize domestic risk factors, and to evaluate how household rodent-proofing interventions could contribute to LF control.

The role of urbanisation in the spread of Aedes mosquitoes and the diseases they transmit-A systematic review.

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 AND FINDINGS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was conducted using the PubMed, Virtual Health Library, Cochrane, WHO Library Database (WHOLIS), Google Scholar, and and the Institutional Repository for Information Sharing (IRIS) databases. From a total of 523 identified studies, 86 were selected for further analysis, and 29 were finally analysed after applying all inclusion and exclusion criteria. The main explanatory variables used to associate urbanisation with epidemiological/entomological outcomes were the following: human population density, urban growth, artificial geographical space, urban construction, and urban density. Associated with the lack of a global definition of urbanisation, several studies provided their own definitions, which represents one of the study's limitations. Results were based on 8 ecological studies/models, 8 entomological surveillance studies, 7 epidemiological surveillance studies, and 6 studies consisting of spatial and predictive models. According to their focus, studies were categorised into 2 main subgroups, namely "Aedes ecology" and "transmission dynamics." There was a consistent association between urbanisation and the distribution and density of Aedes mosquitoes in 14 of the studies and a strong relationship between vector abundance and disease transmission in 18 studies. Human population density of more than 1,000 inhabitants per square kilometer was associated with increased levels of arboviral diseases in 15 of the studies. CONCLUSIONS: The use of different methods in the included studies highlights the interplay of multiple factors linking urbanisation with ecological, entomological, and epidemiological parameters and the need to consider a variety of these factors for designing effective public health approaches.

Systematic review: Yellow fever control through environmental management mechanisms.

OBJECTIVE: Recent research on mosquito vector-borne diseases points to the possibility for a re-emergence of yellow fever. This study investigated attempts at utilising environmental methods and their efficacy for the control of yellow fever and its main vector, Aedes aegypti. METHODS: Potentially eligible studies were searched in Cochrane Library (Reviews and Trials), the Global Index Medicus (encompassing thus the African Index Medicus, the Index Medicus for the Eastern Mediterranean Region, the Index Medicus for the South-East Asia Region, the Latin America and the Caribbean Literature on Health Sciences and the Western Pacific Region Index Medicus), Google Scholar, PubMed and Science Direct. RESULTS: Of a total number of 172 eligible studies, 20 met the pre-defined inclusion criteria. Two of them provided quantitative assessment on the efficacy of the described water management and house screening methods with a reduction of cases of 98%, and of a reduction of larvae of 100%, respectively. The remaining 18 studies described or recommended the elimination of breeding sites (through water or waste management, unspecified, or house destruction), the use of screens for houses and the improvement of air circulation without providing any data to evidence control effectiveness. CONCLUSION: This systematic review provides evidence on the historical use and the perceived effectiveness of environmental management methods for combatting yellow fever. However, these methods would benefit from further investigation via controlled trials to provide data for efficacy, costs, acceptability and feasibility.

Isolation thresholds for curbing SARS-CoV-2 resurgence.

Self-instigated isolation is heavily relied on to curb severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Accounting for uncertainty in the latent and prepatent periods, as well as the proportion of infections that remain asymptomatic, the limits of this intervention at different phases of infection resurgence are estimated. We show that by October 2020, SARS-CoV-2 transmission rates in England had already begun exceeding levels that could be interrupted using this intervention alone, lending support to the second national lockdown on 5th November 2020.

Extreme weather conditions and dengue outbreak in Guangdong, China: Spatial heterogeneity based on climate variability.

BACKGROUND: Previous studies have shown associations between local weather factors and dengue incidence in tropical and subtropical regions. However, spatial variability in those associations remains unclear and evidence is scarce regarding the effects of weather extremes. OBJECTIVES: We examined spatial variability in the effects of various weather conditions on the unprecedented dengue outbreak in Guangdong province of China in 2014 and explored how city characteristics modify weather-related risk. METHODS: A Bayesian spatial conditional autoregressive model was used to examine the overall and city-specific associations of dengue incidence with weather conditions including (1) average temperature, temperature variation, and average rainfall; and (2) weather extremes including numbers of days of extremely high temperature and high rainfall (both used 95th percentile as the cut-off). This model was run for cumulative dengue cases during five months from July to November (accounting for 99.8% of all dengue cases). A further analysis based on spatial variability was used to validate the modification effects by economic, demographic and environmental factors. RESULTS: We found a positive association of dengue incidence with average temperature in seven cities (relative risk (RR) range: 1.032 to 1.153), a positive association with average rainfall in seven cities (RR range: 1.237 to 1.974), and a negative association with temperature variation in four cities (RR range: 0.315 to 0.593). There was an overall positive association of dengue incidence with extremely high temperature (RR:1.054, 95% credible interval (CI): 1.016 to 1.094), without evidence of variation across cities, and an overall positive association of dengue with extremely high rainfall (RR:1.505, 95% CI: 1.096 to 2.080), with seven regions having stronger associations (RR range: 1.237 to 1.418). Greater effects of weather conditions appeared to occur in cities with higher economic level, lower green space coverage and lower elevation. CONCLUSIONS: Spatially varied effects of weather conditions on dengue outbreaks necessitate area-specific dengue prevention and control measures. Extremes of temperature and rainfall have strong and positive associations with dengue outbreaks.

A regional suitable conditions index to forecast the impact of climate change on dengue vectorial capacity.

BACKGROUND: The mosquitoes Aedes aegypti and Ae. albopictus are the primary vectors of dengue virus, and their geographic distributions are predicted to expand further with economic development, and in response to climate change. We aimed to estimate the impact of future climate change on dengue transmission through the development of a Suitable Conditions Index (SCI), based on climatic variables known to support vectorial capacity. We calculated the SCI based on various climate change scenarios for six countries in the Asia-Pacific region (Australia, China, Indonesia, The Philippines, Thailand and Vietnam). METHODS: Monthly raster climate data (temperature and precipitation) were collected for the period January 2005 to December 2018 along with projected climate estimates for the years 2030, 2050 and 2070 using Representative Concentration Pathway (RCP) 4·5, 6·0 and 8·5 emissions scenarios. We defined suitable temperature ranges for dengue transmission of between 17·05-34·61 °C for Ae. aegypti and 15·84-31·51 °C for Ae. albopictus and then developed a historical and predicted SCI based on weather variability to measure the expected geographic limits of dengue vectorial capacity. Historical and projected SCI values were compared through difference maps for the six countries. FINDINGS: Comparing different emission scenarios across all countries, we found that most South East Asian countries showed either a stable pattern of high suitability, or a potential decline in suitability for both vectors from 2030 to 2070, with a declining pattern particularly evident for Ae. albopictus. Temperate areas of both China and Australia showed a less stable pattern, with both moderate increases and decreases in suitability for each vector in different regions between 2030 and 2070. INTERPRETATION: The SCI will be a useful index for forecasting potential dengue risk distributions in response to climate change, and independently of the effects of human activity. When considered alongside additional correlates of infection such as human population density and socioeconomic development indicators, the SCI could be used to develop an early warning system for dengue transmission.

Extreme weather events and dengue outbreaks in Guangzhou, China: a time-series quasi-binomial distributed lag non-linear model.

Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006-2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ≥2 days with temperature ≥ 95th percentile, and extreme rainfall and humidity defined as daily values ≥95th percentile during 2006-2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115-251% around 6 weeks after heatwaves, 173-258% around 6-13 weeks after extremely high rainfall, and 572-587% around 6-13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model's sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks.

Temperature modulates immune gene expression in mosquitoes during arbovirus infection.

The principal vector of dengue, Zika and chikungunya viruses is the mosquito Aedes aegypti, with its ability to transmit pathogens influenced by ambient temperature. We use chikungunya virus (CHIKV) to understand how the mosquito transcriptome responds to arbovirus infection at different ambient temperatures. We exposed CHIKV-infected mosquitoes to 18, 28 and 32°C, and found that higher temperature correlated with higher virus levels, particularly at 3 days post infection, but lower temperature resulted in reduced virus levels. RNAseq analysis indicated significantly altered gene expression levels in CHIKV infection. The highest number of significantly differentially expressed genes was observed at 28°C, with a more muted effect at the other temperatures. At the higher temperature, the expression of many classical immune genes, including Dicer-2, was not substantially altered in response to CHIKV. The upregulation of Toll, IMD and JAK-STAT pathways was only observed at 28°C. Functional annotations suggested that genes in immune response and metabolic pathways related to energy supply and DNA replication were involved in temperature-dependent changes. Time post infection also led to substantially different gene expression profiles, and this varied with temperature. In conclusion, temperature significantly modulates mosquito gene expression in response to infection, potentially leading to impairment of immune defences at higher temperatures.

Repurposing the orphan drug nitisinone to control the transmission of African trypanosomiasis.

Tsetse transmit African trypanosomiasis, which is a disease fatal to both humans and animals. A vaccine to protect against this disease does not exist so transmission control relies on eliminating tsetse populations. Although neurotoxic insecticides are the gold standard for insect control, they negatively impact the environment and reduce populations of insect pollinator species. Here we present a promising, environment-friendly alternative to current insecticides that targets the insect tyrosine metabolism pathway. A bloodmeal contains high levels of tyrosine, which is toxic to haematophagous insects if it is not degraded and eliminated. RNA interference (RNAi) of either the first two enzymes in the tyrosine degradation pathway (tyrosine aminotransferase (TAT) and 4-hydroxyphenylpyruvate dioxygenase (HPPD)) was lethal to tsetse. Furthermore, nitisinone (NTBC), an FDA-approved tyrosine catabolism inhibitor, killed tsetse regardless if the drug was orally or topically applied. However, oral administration of NTBC to bumblebees did not affect their survival. Using a novel mathematical model, we show that NTBC could reduce the transmission of African trypanosomiasis in sub-Saharan Africa, thus accelerating current disease elimination programmes.