Vitamin D testing in children and adolescents in Victoria, Australia: are testing practices in line with global recommendations?

OBJECTIVE: To describe changing primary care ordering of serum 25-hydroxyvitamin D (25OHD) tests in Australian children. DESIGN: Longitudinal, population-based descriptive study of 25OHD testing using a large administrative dataset of pathology orders and results, 2003-2018. SETTING AND PARTICIPANTS: Three primary health networks in Victoria, Australia. Patients aged ≤18 years with a serum 25OHD test ordered by the general practitioner (GP). MAIN OUTCOME MEASURES: Trends over 15 years in the number of 25OHD tests ordered, proportion indicating low levels or vitamin D deficiency and details of repeat testing. RESULTS: Of 970 816 laboratory tests, 61 809 (6.4%) included an order for a 25OHD test. The 61 809 tests were performed in 46 960 children or adolescents. The odds of ordering a 25OHD test in 2018 was 30.4 times higher compared with 2003 (95%CI 22.6 to 40.8, p<0.001). The odds of detecting a low 25OHD (<50 nmol/L) compared with the baseline in 2003 remained steady (adjusted OR<1.5) over time. Repeat tests (14 849) were undertaken in 9626 patients (median intertest interval 357 days, IQR 172-669 days). A total of 4603 test results indicated vitamin D deficiency (<30 nmol/L), but in only 180 (3.9%) of these was a repeat test performed within 3 months as recommended. CONCLUSION: Testing volumes increased 30-fold, but the odds of detecting low 25OHD remained steady. Current Australian policy and the Global Consensus Recommendations for the prevention and management of nutritional rickets do not support routine 25OHD testing. Education and electronic pathology ordering tools may assist GPs to better align practice with current recommendations.

Patient and practice factors associated with HbA1c testing frequency in patients with type 2 diabetes: a retrospective cohort study in Australian general practice.

BACKGROUND: Better adherence to guideline-recommended glycated haemoglobin A1c (HbA1c) testing frequency is associated with better glycaemic control and lower risk of complications such as chronic kidney disease in patients with type 2 diabetes. This study investigates patient and practice factors associated with adherence to guideline-recommended HbA1c testing frequency. METHODS: A cohort of type 2 diabetes patients who regularly visited general practices from 2012 to 2018 was identified from 225 Australian general practices. With the goal of ≤53mmol/mol, Australian guidelines recommend HbA1c testing at least 6-monthly. Patient history of HbA1c tests from 2017 to 2018 was used to define adherence to guidelines, and the associations with patient and practice factors were examined by regression models. RESULTS: Of the 6881 patients, 2186 patients (31.8%) had 6-monthly HbA1c testing. Patient age and anti-diabetic medications were associated with adherence to 6-monthly testing. When financial incentives are available to practices, a larger practice was associated with better adherence to 6-monthly testing. CONCLUSIONS: The identified key factors such as age, practice size, medication, and incentive payments can be used to target initiatives aimed at improving guideline-recommended monitoring care for patients with type 2 diabetes to enhance their health outcomes.

A framework for conducting policy-relevant primary care research: a COVID-19 case study in Australia.

The onset of the coronavirus disease 2019 (COVID-19) pandemic, caused by SARS-CoV-2, and the ensuing implementation of response measures directly impacted the delivery of Australian primary care services. Understanding how these measures affected practice activity is important for gauging both their effectiveness and implications for future service planning. During the first 2years of the COVID-19 pandemic, a research project was undertaken to determine the impact of the pandemic on Australian general practice activity as a collaborative undertaking between researchers, general practitioners, data custodians, and five primary health networks from New South Wales and Victoria, Australia. The project methodology was based on an established research approach called action research, which involves participatory involvement from key stakeholders throughout the research process. The strength and success of the project's methodological approach stemmed from the synergistic interrelationship between the four key elements of: collaboration, repeated action research cycles (utilising electronic general practice data), engaged governance, and the production and dissemination of apposite knowledge outcomes. The project approach, knowledge outputs and lessons learned can be adapted to future research undertakings across any primary care setting and highlight the utility of action research and interdisciplinary research collaboration to produce knowledge directly relevant to clinical practice.

Telehealth use in patients with type 2 diabetes in Australian general practice during the COVID-19 pandemic: a retrospective cohort study.

BACKGROUND: The Australian government introduced temporary government-subsidised telehealth service items (phone and video-conference) in mid-March 2020 in response to the COVID-19 pandemic. The uptake of telehealth by patients with type 2 diabetes (T2DM) for consulting with GPs is unknown. AIM: To evaluate the uptake of telehealth consultations and associated patient characteristics in Australian general practice, including the frequency of haemoglobin A1c (HbA1c) tests and change in HbA1c levels by telehealth use, compared with guideline recommendations. DESIGN & SETTING: This exploratory study used electronic patient data from approximately 800 general practices in Victoria and New South Wales (NSW), Australia. A pre-COVID-19 period from March 2019-February 2020 was compared with a pandemic period from March 2020-February 2021. Patients diagnosed with T2DM before March 2018 were included. METHOD: Telehealth uptake patterns were examined overall and by patient characteristics. Generalised estimating equation models were used to examine patient probability of 6-monthly HbA1c testing and change in HbA1c levels, comparing between patients who did and patients who did not use telehealth. RESULTS: Of 57 916 patients, 80.8% had telehealth consultations during the pandemic period. Telehealth consultations were positively associated with patients with T2DM who were older, female, had chronic kidney disease (CKD), prescribed antidiabetic medications, and living in remote areas. No significant difference was found in 6-monthly HbA1c testing and HbA1c levels between telehealth users and patients who had face-to-face consultations only. CONCLUSION: Telehealth GP consultations were well utilised by patients with T2DM. Diabetes monitoring care via telehealth is as effective as face-to-face consultations.

Telehealth-based diagnostic testing in general practice during the COVID-19 pandemic: an observational study.

BACKGROUND: Since the World Health Organization declared COVID-19 a pandemic on 11 March 2020, health technologies have been rapidly scaled up to ensure access to care. A significant innovation has been telehealth in general practice. Now widespread, it remains unknown how this shift to virtual care has impacted on quality-of-care indicators such as pathology testing and diagnosis. AIM: To undertake a comparison of telehealth and face-to-face general practice consultations to: identify if there were differences in the proportion of pathology test referrals from 2019-2020; and quantify any change in pathology test collection and follow-up patterns. DESIGN & SETTING: Retrospective observational study of routinely collected electronic patient data from 807 general practices across New South Wales (NSW) and Victoria, Australia. METHOD: Multivariate generalised estimating equation models were used to estimate the proportion of pathology test referrals for overall, face-to-face, and telehealth consultations. Pathology test follow-up was described through median (and interquartile range [IQR]) time. RESULTS: Pathology test referrals declined during periods of high COVID-19 cases, falling from 10.8% in February 2020 to a low of 4.5% during the first peak in April. Overall, pathology test referrals were lower for telehealth than face-to-face consultations. Median time between referral and test collection was 3 days (IQR 1-14) for telehealth and 1 day (IQR 0-7) for face to face. CONCLUSION: For telehealth to become part of routine care, it is crucial that gaps in functionality, including difficulty in test referral processes, be addressed. Quality improvements supporting care practices will ensure clinicians' workflows are supported and patients receive diagnostic testing.

COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy-a design thinking approach.

BACKGROUND: Health systems around the world have been forced to make choices about how to prioritize care, manage infection control and maintain reserve capacity for future disease outbreaks. Primary healthcare has moved into the front line as COVID-19 testing transitions from hospitals to multiple providers, where tracking testing behaviours can be fragmented and delayed. Pooled general practice data are a valuable resource which can be used to inform population and individual care decision-making. This project aims to examine the feasibility of using near real-time electronic general practice data to promote effective care and best-practice policy. METHODS: The project will utilize a design thinking approach involving all collaborators (primary health networks [PHNs], general practices, consumer groups, researchers, and digital health developers, pathology professionals) to enhance the development of meaningful and translational project outcomes. The project will be based on a series of observational studies utilizing near real-time electronic general practice data from a secure and comprehensive digital health platform [POpulation Level Analysis and Reporting (POLAR) general practice data warehouse]. The study will be carried out over 1.5 years (July 2020-December 2021) using data from over 450 general practices within three Victorian PHNs and Gippsland PHN, Eastern Melbourne PHN and South Eastern Melbourne PHN, supplemented by data from consenting general practices from two PHNs in New South Wales, Central and Eastern Sydney PHN and South Western Sydney PHN. DISCUSSION: The project will be developed using a design thinking approach, leading to the building of a meaningful near real-time COVID-19 geospatial reporting framework and dashboard for decision-makers at community, state and nationwide levels, to identify and monitor emerging trends and the impact of interventions/policy decisions. This will integrate timely evidence about the impact of the COVID-19 pandemic related to its diagnosis and treatment, and its impact across clinical, population and general practice levels.

Adherence to guideline-recommended HbA1c testing frequency and better outcomes in patients with type 2 diabetes: a 5-year retrospective cohort study in Australian general practice.

BACKGROUND: Clinical practice guidelines emphasise the role of regular monitoring of glycated haemoglobin A1c (HbA1c) for patients with type 2 diabetes, with most recommending 6-monthly testing. Nonetheless, there are few in-depth studies evaluating the clinical impact of the recommended testing frequency for patients to underpin the significance of guideline adherence. OBJECTIVE: This study aimed to examine associations between patient outcomes and adherence to HbA1c testing frequencies recommended by Australian guidelines (6-monthly for patients with adequate glycaemic control and 3-monthly for patients with inadequate glycaemic control). The primary and secondary outcomes of interest were longitudinal changes in HbA1c values and development of ischaemic heart disease (IHD) and chronic kidney disease (CKD). METHODS: This 5-year retrospective cohort study (July 2013-June 2018) evaluated HbA1c testing frequency in a subset of patients with type 2 diabetes identified within data collected from approximately 250 Australian general practices. The study included patients who were aged ≥18 in 2013 and had a record of HbA1c testing in study practices during the study period. Each patient's adherence rate was defined by the proportion of HbA1c tests performed within the testing intervals recommended by Australian guidelines. Based on the adherence rate, adherence level was categorised into low (≤33%), moderate (34%-66%) and high (>66%). Generalised additive mixed models were used to examine associations between adherence to the recommended HbA1c testing frequency and patient outcomes. RESULTS: In the 6424 patients with diabetes, the overall median HbA1c testing frequency was 1.6 tests per year with an adherence rate of 50%. The estimated HbA1c levels among patients with low adherence gradually increased or remained inadequately controlled, while HbA1c values in patients with high adherence remained controlled or improved over time. The risk of developing CKD for patients with high adherence was significantly lower than for patients with low adherence (OR: 0.42, 95% CI 0.18 to 0.99). No association between IHD and adherence to the recommended HbA1c frequency was observed. CONCLUSION: Better adherence to guideline-recommended HbA1c testing frequency was associated with better glycaemic control and lower risk of CKD. These findings may provide valuable evidence to support the use of clinical guidelines for better patient outcomes in patients with type 2 diabetes.

Harnessing the potential of electronic general practice pathology data in Australia: An examination of the quality use of pathology for type 2 diabetes patients.

BACKGROUND: Despite the importance of pathology testing in diagnosis and disease monitoring, there is little in-depth research about pathology test ordering in general practice and how it impacts patient outcomes. This is in part due to the limited availability of high-quality data. With the now-widespread use of electronic software in general practice comes the potential for electronic patient data to be used for research leading to better understanding of general practice activities, including pathology testing. OBJECTIVES: This study aimed to examine the usefulness of electronic general practice pathology data to: (1) identify patients' characteristics, (2) monitor quality of care, (3) evaluate intervention effects, (4) identify variations in patient care, and (5) measure patient outcomes. An exemplar study evaluating kidney function testing in type 2 diabetes mellitus (type 2 diabetes) compared to guidelines was used to demonstrate the value of pathology data. MATERIALS AND METHODS: De-identified electronic data from approximately 200 general practices in Victoria were extracted using Outcome Health's Population Level Analysis & Reporting (POLAR) Aurora research platform. Our study population included patients ≥18 diagnosed with type 2 diabetes before July 2016. Data from July 2016 to June 2018 were used to i) determine frequency of kidney function tests (KFT), and ii) identify whether antihypertensive medications were prescribed for abnormal KFT results. RESULTS: There were 20,514 active patients with type 2 diabetes identified from the data. The age and gender standardised estimate of diabetes prevalence was 4.9%, consistent with Australian estimates (5.2%). Sociodemographic features of prevalence, including higher prevalence in older males, were also consistent with previous Australian estimates. Kidney function testing was performed annually, as recommended by guidelines, in 75.7% of patients, with higher annual testing observed in patients managed under general practice incentive programs (80.1%) than those who were not (72.2%). Antihypertensive medications were prescribed as recommended in 77.4% of patients with suspected microalbuminuria or macroalbuminuria based on KFT results. DISCUSSION: Evaluations using data from diabetes patients in this study illustrate the value of electronic data for identifying patients with the condition of interest (e.g. type 2 diabetes) along with sociodemographic characteristics. This allows for the ability to undertake analyses on pathology testing factors and the identification of variation compared to guidelines, which has a potential to ensure quality of care. Its potential to identify associations with incentive programs further demonstrates the advantages of the data's longitudinal nature. These include the ability to assess temporal order and time interval of tests as a marker of quality of monitoring and evaluate intervention effects on a cohort over time. Finally, analyses on antihypertensive medication prescribing in patients with suspected micro/macroalbuminuria exemplified the electronic data's usefulness in monitoring patient outcomes, such as appropriate prescribing based on pathology test results. CONCLUSIONS: Electronic general practice data is an important resource which can provide valuable insights about the quality use of pathology. There are clear benefits to patients for better monitoring, and consequent better outcomes, and to inform policymakers about the best ways to channel resources to enhance the quality of care.

Publisher Correction: Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Presenteeism among health care workers with laboratory-confirmed influenza infection: A retrospective cohort study in Queensland, Australia.

BACKGROUND: A high prevalence of working while ill (presenteeism) has been documented among health care workers (HCWs). However, previous evidence is primarily based on nonspecific causes of sickness and self-reported data. Our study examined presenteeism among HCWs with laboratory-confirmed influenza. METHODS: The data pertaining to laboratory-confirmed influenza cases and history of sick leave among HCWs in Queensland, Australia, were collected from 2009-2015. The incidence and duration of sick leave around the time of disease confirmation were analyzed. The associations of factors, such as job category and employment status, on presenteeism were assessed with regression analyses. RESULTS: The overall sick leave incidence was 85.9% in the laboratory-confirmed periods, which translates that 14.1% of HCWs were working while ill with influenza. Among medical doctors, approximately one-quarter of them were attending work in the period. A shorter duration of leave was also observed among medical doctors and full-time employees compared with other HCWs and part-time employees. CONCLUSIONS: Presenteeism among HCWs with influenza put both HCWs and patients at risk by increasing potential for transmission. Our findings emphasize the importance of an integrated approach including both HCW sick leave management and vaccination for strategic prevention and control of nosocomial influenza infection.

Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model.

Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r > 0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r > 0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.

A systematic review and meta-analysis of the direct epidemiological and economic effects of seasonal influenza vaccination on healthcare workers.

BACKGROUND: Influenza vaccination is a commonly used intervention to prevent influenza infection in healthcare workers (HCWs) and onward transmission to other staff and patients. We undertook a systematic review to synthesize the latest evidence of the direct epidemiological and economic effectiveness of seasonal influenza vaccination among HCW. METHODS: We conducted a systematic search of MEDLINE/PubMed, Scopus, and Cochrane Central Register of Controlled Trials from 1980 through January 2018. All studies comparing vaccinated and non-vaccinated (i.e. placebo or non-intervention) groups of HCWs were included. Research articles that focused on only patient-related outcomes or monovalent A(H1N1)pdm09 vaccines were excluded. Two reviewers independently selected articles and extracted data. Pooled-analyses were conducted on morbidity outcomes including laboratory-confirmed influenza, influenza-like illnesses (ILI), and absenteeism. Economic studies were summarized for the characteristics of methods and findings. RESULTS: Thirteen articles met eligibility criteria: three articles were randomized controlled studies and ten were cohort studies. Pooled results showed a significant effect on laboratory-confirmed influenza incidence but not ILI. While the overall incidence of absenteeism was not changed by vaccine, ILI absenteeism was significantly reduced. The duration of absenteeism was also shortened by vaccination. All published economic evaluations consistently found that the immunization of HCW was cost saving based on crude estimates of avoided absenteeism by vaccination. No studies, however, comprehensively evaluated both health outcomes and costs of vaccination programs to examine cost-effectiveness. DISCUSSION: Our findings reinforced the influenza vaccine effects in reducing infection incidence and length of absenteeism. A better understanding of the incidence of absenteeism and comprehensive economic program evaluations are required to ensure the best possible management of ill HCWs and the investment in HCW immunization in increasingly constrained financial environments. These steps are fundamental to establish sustainability and cost-effectiveness of vaccination programs and underpin HCW immunization policy.

Diarrheal Diseases and Climate Change in Cambodia.

The DRIP-SWICCH (Developing Research and Innovative Policies Specific to the Water-related Impacts of Climate Change on Health) project aimed to increase the resilience of Cambodian communities to the health risks posed by climate change-related impacts on water. This article follows a review of climate change and water-related diseases in Cambodia and presents the results of a time series analysis of monthly weather and diarrheal disease data for 11 provinces. In addition, correlations of diarrheal disease incidence with selected demographic, socioeconomic, and water and sanitation indicators are described, with results suggesting education and literacy may be most protective against disease. The potential impact of climate change on the burden of diarrheal disease in Cambodia is considered, along with the implications of these findings for health systems adaptation.

Associations between malaria and local and global climate variability in five regions in Papua New Guinea.

BACKGROUND: Malaria is a significant public health issue in Papua New Guinea (PNG) as the burden is among the highest in Asia and the Pacific region. Though PNG's vulnerability to climate change and sensitivity of malaria mosquitoes to weather are well-documented, there are few in-depth epidemiological studies conducted on the potential impacts of climate on malaria incidence in the country. METHODS: This study explored what and how local weather and global climate variability impact on malaria incidence in five regions of PNG. Time series methods were applied to evaluate the associations of malaria incidence with weather and climate factors, respectively. Local weather factors including precipitation and temperature and global climate phenomena such as El Niño-Southern Oscillation (ENSO), the ENSO Modoki, the Southern Annular Mode, and the Indian Ocean Dipole were considered in analyses. RESULTS: The results showed that malaria incidence was associated with local weather factors in most regions but at the different lag times and in directions. Meanwhile, there were trends in associations with global climate factors by geographical locations of study sites. CONCLUSIONS: Overall heterogeneous associations suggest the importance of location-specific approaches in PNG not only for further investigations but also public health interventions in repose to the potential impacts arising from climate change.

The Role of Influenza in the Delay between Low Temperature and Ischemic Heart Disease: Evidence from Simulation and Mortality Data from Japan.

Many studies have found that cardiovascular deaths mostly occur within a few days of exposure to heat, whereas cold-related deaths can occur up to 30 days after exposure. We investigated whether influenza infection could explain the delayed cold effects on ischemic heart diseases (IHD) as they can trigger IHD. We hypothesized two pathways between cold exposure and IHD: a direct pathway and an indirect pathway through influenza infection. We created a multi-state model of the pathways and simulated incidence data to examine the observed delayed patterns in cases. We conducted cross-correlation and time series analysis with Japanese daily pneumonia and influenza (P&I) mortality data to help validate our model. Simulations showed the IHD incidence through the direct pathway occurred mostly within 10 days, while IHD through influenza infection peaked at 4-6 days, followed by delayed incidences of up to 20-30 days. In the mortality data from Japan, P&I lagged IHD in cross-correlations. Time series analysis showed strong delayed cold effects in the older population. There was also a strong delay on intense days of influenza which was more noticeable in the older population. Influenza can therefore be a plausible explanation for the delayed association between cold exposure and cardiovascular mortality.

Time series regression model for infectious disease and weather.

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context.

A systematic review of methodology: time series regression analysis for environmental factors and infectious diseases.

BACKGROUND: Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. FINDINGS: Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. CONCLUSION: The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases.

Tropical influenza and weather variability among children in an urban low-income population in Bangladesh.

BACKGROUND: Influenza seasonality in the tropics is poorly understood and not as well documented as in temperate regions. In addition, low-income populations are considered highly vulnerable to such acute respiratory disease, owing to limited resources and overcrowding. Nonetheless, little is known about their actual disease burden for lack of data. We therefore investigated associations between tropical influenza incidence and weather variability among children under five in a poor urban area of Dhaka, Bangladesh. DESIGN: Acute respiratory illness data were obtained from a population-based respiratory and febrile illness surveillance dataset of Kamalapur, a low-income urban area in southeast Dhaka. Analyzed data were from January 2005 through December 2008. Nasopharyngeal wash specimens were collected from every fifth eligible surveillance participant during clinic visits to identify influenza virus infection with viral culture and reverse transcriptase-polymerase chain reaction. Time series analysis was conducted to determine associations between the number of influenza cases per week and weather factors. Zero-inflated Poisson and generalized linear Poisson models were used in the analysis for influenza A and B, respectively. RESULTS: Influenza A had associations with minimum temperature, relative humidity (RH), sunlight duration, and rainfall, whereas only RH was associated with influenza B. Although associations of the other weather factors varied between the two subtypes, RH shared a similar positive association when humidity was approximately 50-70%. CONCLUSIONS: Our findings of a positive RH association is consistent with prior studies, and may suggest the viral response in the tropics. The characteristics of settlement areas, population demographics, and typical overcrowding of urban poverty may also contribute to different impacts of rainfall from higher economic population. Further investigations of associations between tropical influenza and weather variability for urban low-income populations are required for better understanding.