Meteorological factors affecting dengue incidence in Davao, Philippines

BackgroundDengue fever is a major public health concern in the Philippines, and has been a significant cause of hospitalizations and deaths among young children. Previous literature links climate change to dengue, and with increasingly unpredictable changing climate patterns, there is a need to understand how these meteorological variables affect dengue incidence in a highly endemic area.MethodsWeekly dengue incidences (2011–2015) in Davao Region, Philippines were obtained from the Department of Health. Same period of weekly local meteorological variables were obtained from the National Climatic Data Center (NCDC) and the National Oceanic and Atmospheric Administration (NOAA). Wavelet coherence analysis was used to determine the presence of non-stationary relationships, while a quasi-Poisson regression combined with distributed lag nonlinear model (DLNM) was used to analyze the association between meteorological variables and dengue incidences.ResultsSignificant periodicity was detected in the 7 to 14-week band between the year 2011–2012 and a 26-week periodicity from the year 2013–2014. Overall cumulative risks were particularly high for rainfall at 32 mm (RR: 1.67, 95% CI: 1.07–2.62), while risks were observed to increase with increasing dew point. On the other hand, lower average temperature of 26 °C has resulted to an increased RR of dengue (RR: 1.96, 95% CI: 0.47–8.15) while higher temperature from 27 °C to 31 °C has lower RR.ConclusionsThe observed possible threshold levels of these meteorological variables can be integrated into an early warning system to enhance dengue prediction for better vector control and management in the future

Effect modification in the temperature extremes by mortality subgroups among the tropical cities of the Philippines

BackgroundTemperature–mortality relationships have been extensively probed with varying temperature range but with relatively similar patterns and in some instances are being modified by specific mortality groups such as causes of mortality, sex, and age.ObjectiveThis study aimed to determine the risk attributions in the extreme temperatures and also identified the risks associated with the various mortality subgroups.DesignWe used the 2006–2010 daily average meteorological and daily mortality variables from the Philippine Atmospheric Geophysical and Astronomical Services Administration and Philippine Statistics Authority–National Statistics Office, respectively. Mortality data were divided according to cause (cardiovascular and respiratory), sex, and age (0–14 years, 15–64 years, and >64 years). We performed a two-stage analysis to estimate the extreme temperature effects stratified by the different mortality subgroups to observe the effect modification.ResultsIn the pooled analysis, greater risks were observed in the extreme high temperature (99th temperature percentile; RR (relative risk)=2.48 CI: 1.55–3.98) compared to the extreme low temperature (1st temperature percentile; RR=1.23 CI: 0.88–1.72). Furthermore, effect modification by mortality subgroups was evident, especially higher risks for extreme temperatures with respiratory-related diseases, women, and elderly.ConclusionsBoth sex and age were found to effect modify the risks in extreme temperatures of tropical cities; hence, health-related policies should take these risk variations into consideration to create strategies with respect to the risk population

Assessing frontline HIV service provider efficiency using data envelopment analysis: a case study of Philippine social hygiene clinics (SHCs)

AbstractBackground:Globally, local and frontline HIV service delivery units have been deployed to halt the HIV epidemic.However, with the limited resources, there is a need to understand how these units can deliver their optimumoutputs/outcomes efficiently given the inputs. This study aims to determine the efficiency of the social hygieneclinics (SHC) in the Philippines as well as to determine the association of the meta-predictor to the efficiencies.Methods:In determining efficiency, we used the variables from two data sources namely the 2012 Philippine HIVCosting study and 2011 Integrated HIV Behavioral and Serologic Surveillance, as inputs and outputs, respectively.Various data management protocols and initial assumptions in data matching, imputation and variable selection,were used to create the final dataset with 9 SHCs. We used data envelopment analysis (DEA) to analyse theefficiency, while variations in efficiencies were analysed using Tobit regression with area-specific meta-predictors.Results:There were potentially inefficient use of limited resources among sampled SHC in both aggregate and keypopulations. Tobit regression results indicated that income was positively associated with efficiency, while HIVprevalence was negatively associated with the efficiency variations among the SHCs.Conclusions:We were able to determine the inefficiently performing SHCs in the Philippines. Though currentlyinefficient, these SHCs may adjust their inputs and outputs to become efficient in the future. While there wereindications of income and HIV prevalence to be associated with the efficiency variations, the results of this casestudy may only be limited in generalisability, thus further studies are warranted

Associations between ambient temperature and enteric infections by pathogen: a systematic review and meta-analysis

Background: Numerous studies have quantified the associations between ambient temperature and enteric infections, particularly all-cause enteric infections. However, the temperature sensitivity of enteric infections might be pathogen dependent. Here, we sought to identify pathogen-specific associations between ambient temperature and enteric infections.Methods: We did a systematic review and meta-analysis by searching PubMed, Web of Science, and Scopus for peerreviewed research articles published from Jan 1, 2000, to Dec 31, 2019, and also hand searched reference lists of included articles and excluded reviews. We included studies that quantified the effects of ambient temperature increases on common pathogen-specific enteric infections in humans. We excluded studies that expressed ambient temperature as a categorical or diurnal range, or in a standardised format. Two authors screened the search results, one author extracted data from eligible studies, and four authors verified the data. We obtained the overall risks by pooling the relative risks of enteric infection by pathogen for each 1°C temperature rise using random-effects modelling and robust variance estimation for the correlated effect estimates. Between-study heterogeneity was measured using I², τ², and Q-statistic. Publication bias was determined using funnel plot asymmetry and the trimand-fill method. Differences among pathogen-specific pooled estimates were determined using subgroup analysis of taxa-specific meta-analysis. The study protocol was not registered but followed the PRISMA guidelines.Findings: We identified 2981 articles via database searches and 57 articles from scanning reference lists of excluded reviews and included articles, of which 40 were eligible for pathogen-specific meta-analyses. The overall increased risks of incidence per 1°C temperature rise, expressed as relative risks, were 1·05 (95% CI 1·04–1·07; I² 97%) for salmonellosis, 1·07 (1·04–1·10; I² 99%) for shigellosis, 1·02 (1·01–1·04; I² 98%) for campylobacteriosis, 1·05 (1·04–1·07; I² 36%) for cholera, 1·04 (1·01–1·07; I² 98%) for Escherichia coli enteritis, and 1·15 (1·07–1·24; I² 0%) for typhoid. Reduced risks per 1°C temperature increase were 0·96 (95% CI 0·90–1·02; I² 97%) for rotaviral enteritis and 0·89 (0·81–0·99; I² 96%) for noroviral enteritis. There was evidence of between-pathogen differences in risk for bacterial infections but not for viral infections.Interpretation: Temperature sensitivity of enteric infections can vary according to the enteropathogen causing the infection, particularly for bacteria. Thus, we encourage a pathogen-specific health adaptation approach, such as vaccination, given the possibility of increasingly warm temperatures in the future

Characteristics of COVID-19 epidemic and control measures to curb transmission in Malaysia

The first wave of COVID-19 epidemic began in late January in Malaysia and ended with a very small size. The second wave of infections broke out in late February and grew rapidly in the first 3 weeks. Authorities in the country responded quickly with a series of control strategies collectively known as the Movement Control Order (MCO) with different levels of intensity matching the progression of the epidemic. We examined the characteristics of the second wave and discussed the key control strategies implemented in the country. In the second wave, the epidemic doubled in size every 3.8 days (95% confidence interval: 3.3, 4.5) in the first month and decayed slowly after that with a halving time of approximately 3 weeks. The time-varying reproduction number Rt peaked at 3.1 (95% credible interval: 2.7, 3.5) in the 3rd week, declined sharply thereafter and stayed below 1 in the last 3 weeks of April,indicating low transmissibility approximately 3 weeks after the MCO. The experience of Malaysia suggests that adaptive triggering of distancing policies combined with a population-wide movement control measure can be effective in suppressing transmission and preventing a rebound

Global projections of temperature-attributable mortality due to enteric infections: a modelling study

Background: Mortality due to enteric infections is projected to increase because of global warming; however, the different temperature sensitivities of major enteric pathogens have not yet been considered in projections on a global scale. We aimed to project global temperature-attributable enteric infection mortality under various future scenarios of sociodemographic development and climate change.Methods: In this modelling study, we generated global projections in two stages. First, we forecasted baseline mortality from ten enteropathogens (non-typhoidal salmonella, Shigella, Campylobacter, cholera, enteropathogenic Escherichia coli, enterotoxigenic E coli, typhoid, rotavirus, norovirus, and Cryptosporidium) under several future sociodemographic development and health investment scenarios (ie, pessimistic, intermediate, and optimistic). We then estimated the mortality change from baseline attributable to global warming using the product of projected annual temperature anomalies and pathogen-specific temperature sensitivities.Findings: We estimated that in the period 2080–95, the global mean number of temperature-attributable deaths due to enteric infections could be as low as 6599 (95% empirical CI 5441–7757) under the optimistic sociodemographic development and climate change scenario, or as high as 83 888 (67 760–100 015) under the pessimistic scenario. Most of the projected temperature-attributable deaths were from shigellosis, cryptosporidiosis, and typhoid fever in sub-Saharan Africa and South Asia. Considerable reductions in the number of attributable deaths were from viral infections, such as rotaviral and noroviral enteritis, which resulted in net reductions in attributable enteric infection mortality under optimistic scenarios for Latin America and the Caribbean and East Asia and the Pacific.Interpretation: Temperature-attributable mortality could increase under warmer climate and unfavourable sociodemographic conditions. Mitigation policies for limiting global warming and sociodemographic development policies for low-income and middle-income countries might help reduce mortality from enteric infections in the future.Funding: Japan Society for the Promotion of Science, Japan Science and Technology Agency, and Spanish Ministry of Economy, Industry, and Competitiveness

Quantifying Excess Deaths Related to Heatwaves under Climate Change Scenarios: A multicountry time series modelling study

Background: Heatwaves are a critical public health problem. There will be an increase in the frequency and severity of heatwaves under changing climate. However, evidence about the impacts of climate change on heatwave-related mortality at a global scale is limited. Methods and findings: We collected historical daily time series of mean temperature and mortality for all causes or nonexternal causes, in periods ranging from January 1, 1984, to December 31, 2015, in 412 communities within 20 countries/regions. We estimated heatwave–mortality associations through a two-stage time series design. Current and future daily mean temperature series were projected under four scenarios of greenhouse gas emissions from 1971–2099, with five general circulation models. We projected excess mortality in relation to heatwaves in the future under each scenario of greenhouse gas emissions, with two assumptions for adaptation (no adaptation and hypothetical adaptation) and three scenarios of population change (high variant, median variant, and low variant). Results show that, if there is no adaptation, heatwave-related excess mortality is expected to increase the most in tropical and subtropical countries/regions (close to the equator), while European countries and the United States will have smaller percent increases in heatwave-related excess mortality. The higher the population variant and the greenhouse gas emissions, the higher the increase of heatwave-related excess mortality in the future. The changes in 2031–2080 compared with 1971–2020 range from approximately 2,000% in Colombia to 150% in Moldova under the highest emission scenario and high-variant population scenario, without any adaptation. If we considered hypothetical adaptation to future climate, under high-variant population scenario and all scenarios of greenhouse gas emissions, the heatwave-related excess mortality is expected to still increase across all the countries/regions except Moldova and Japan. However, the increase would be much smaller than the no adaptation scenario. The simple assumptions with respect to adaptation as follows: no adaptation and hypothetical adaptation results in some uncertainties of projections. Conclusions: This study provides a comprehensive characterisation of future heatwave-related excess mortality across various regions and under alternative scenarios of greenhouse gas emissions, different assumptions of adaptation, and different scenarios of population change. The projections can help decision makers in planning adaptation and mitigation strategies for climate change. © 2018 Guo et al. http://creativecommons.org/licenses/by/4.0/

Temperature-Related Mortality Impacts Under and Beyond Paris Agreement Climate Change Scenarios

The Paris Agreement binds all nations to undertake ambitious efforts to combat climate change, with the commitment to Bhold warming well below 2 °C in global mean temperature (GMT), relative to pre-industrial levels, and to pursue efforts to limit warming to 1.5 °C^. The 1.5 °C limit constitutes an ambitious goal for which greater evidence on its benefits for health would help guide policy and potentially increase the motivation for action. Here we contribute to this gap with an assessment on the potential health benefits, in terms of reductions in temperature-related mortality, derived from the compliance to the agreed temperature targets, compared to more extreme warming scenarios. We performed a multi-region analysis in 451 locations in 23 countries with different climate zones, and evaluated changes in heat and coldrelated mortality under scenarios consistent with the Paris Agreement targets (1.5 and 2 °C) and more extreme GMT increases (3 and 4 °C), and under the assumption of no changes in demographic distribution and vulnerability. Our results suggest that limiting warming below 2 °C could prevent large increases in temperature-related mortality in most regions worldwide. The comparison between 1.5 and 2 °C is more complex and characterized by higher uncertainty, with geographical differences that indicate potential benefits limited to areas located in warmer climates, where direct climate change impacts will be more discernible

Temperature-Related Mortality Impacts Under and Beyond Paris Agreement Climate Change Scenarios

The Paris Agreement binds all nations to undertake ambitious efforts to combat climate change, with the commitment to Bhold warming well below 2 °C in global mean temperature (GMT), relative to pre-industrial levels, and to pursue efforts to limit warming to 1.5 °C^. The 1.5 °C limit constitutes an ambitious goal for which greater evidence on its benefits for health would help guide policy and potentially increase the motivation for action. Here we contribute to this gap with an assessment on the potential health benefits, in terms of reductions in temperature-related mortality, derived from the compliance to the agreed temperature targets, compared to more extreme warming scenarios. We performed a multi-region analysis in 451 locations in 23 countries with different climate zones, and evaluated changes in heat and coldrelated mortality under scenarios consistent with the Paris Agreement targets (1.5 and 2 °C) and more extreme GMT increases (3 and 4 °C), and under the assumption of no changes in demographic distribution and vulnerability. Our results suggest that limiting warming below 2 °C could prevent large increases in temperature-related mortality in most regions worldwide. The comparison between 1.5 and 2 °C is more complex and characterized by higher uncertainty, with geographical differences that indicate potential benefits limited to areas located in warmer climates, where direct climate change impacts will be more discernible

Evaluating the Effects of Temperature on Mortality in Manila City (Philippines) from 2006–2010 Using a Distributed Lag Nonlinear Model

The effect of temperature on the risk of mortality has been described in numerous studies of category-specific (e.g., cause-, sex-, age-, and season-specific) mortality in temperate and subtropical countries, with consistent findings of U-, V-, and J-shaped exposure-response functions. In this study, we analyzed the relationship between temperature and mortality in Manila City (Philippines), during 2006–2010 to identify the potential susceptible populations. We collected daily all-cause and cause-specific death counts from the Philippine Statistics Authority-National Statistics Office and the meteorological variables were collected from the Philippine Atmospheric Geophysical and Astronomical Services Administration. Temperature-mortality relationships were modeled using Poisson regression combined with distributed lag nonlinear models, and were used to perform cause-, sex-, age-, and season-specific analyses. The minimum mortality temperature was 30 °C, and increased risks of mortality were observed per 1 °C increase among elderly persons (RR: 1.53, 95% CI: 1.31–1.80), women (RR: 1.47, 95% CI: 1.27–1.69), and for respiratory causes of death (RR: 1.52, 95% CI: 1.23–1.88). Seasonal effect modification was found to greatly affect the risks in the lower temperature range. Thus, the temperature-mortality relationship in Manila City exhibited an increased risk of mortality among elderly persons, women, and for respiratory-causes, with inherent effect modification in the season-specific analysis. The findings of this study may facilitate the development of public health policies to reduce the effects of air temperature on mortality, especially for these high-risk groups