Problems of irrational antibiotic use by prescribers are ongoing and have escalated following reductions in the cost of essential drugs policy. In an attempt to improve prescribing practices for village doctors and rational use of essential drugs, a program designed to audit and monitor drug use was established. However, the effects of the program to control antibiotic resistance and changing the village doctors’ prescribing behaviors remain largely unknown. This study measured the effect of the program on levels of antibiotic use.Data was collected covering a 22-month period, before, during and after the program was implemented in rural clinics. Segmented regression analysis with interrupted time series (ITS) data was used to examine whether there had been a significant interaction with the onset of the program in September 2011 and levels of antibiotic use from November 2010 to August 2012. Both serial and 12-month lag autocorrelations were controlled for.P = 0.089) for the antibiotic use in outpatients, which is lower of effect size assuming that the program has the immediate impact of the program were captured for the immediate effect of the program. Meanwhile, levels of antibiotic use would have continued to decrease by 1.12% per month (P = 0.034) as they did in the absence of the program.A noticeable drop about 6.15% per month  in antibiotic use after its implementation.The central finding was that the prescription audit and feedback program was associated with significant decreases ( The first release of surveillance data on antibiotic resistance of the WHO published in January 2018 highlighted the threat posed by antibiotic resistance to the worldwide. It revealed that around 500,000 people with suspected bacterial infections among 22 countries , 4. ThesSince China started the economic reform in 1978, coverage of health care benefits shank dramatically. Health care facilities stopped receiving state funding since 1980 and began to operate a fee for service model. Physicians had to operate on patient fees, generating income by provision of services and usage of medicines. The more procedures they perform, the more pay checks physicians will get. Fee for service model put both rural and urban residents into vulnerability. It is inevitable that more drugs than needed and higher profit drugs have been prescribed for revenue, and antibiotic sales accounted for a rather large proportion. To address over-prescription of antibiotics, different approaches have been introduced in an attempt over recent years , such asIn order to prevent physicians applying the fee for service model and improve the quality of prescribing, Huangdao Bureau of Health introduced a prescription audit and feedback plan——the Rural Clinics Prescription Comment (RCPC). This RCPC program separated physicians’ income from prescription drug sales through regulations but with prescribing behaviors. Since September 1st, 2011 the Prescription Comment Working Group (PCWG) has produced the RCPC program every two weeks through the prescription comment working platform. The PCWG is composed of clinical pharmacologists and experienced clinicians, who were selected from town hospitals. The town hospitals are the leading institutions of the rural clinics. The rural clinics are state-owned institutions providing primary care to approximately 800,000 inhabitants of the Huangdao District. The process proceeded as follows and was also presented in Fig. The aim of the study is to employ interrupted time series (ITS) methods to investigate the effects on the usage of antibiotics of the introduction of such an approach in Huangdao District of Qingdao in Shandong Province.This is a full-coverage, nonrandomized study of a primary health care intervention designed to analyze the impact of the RCPC program on antibiotic prescribing practices in outpatients. As all the rural clinics received this intervention, there is no control group. So this study applies a pre-experimental study design. In all cases, the outcome was observed every month continuously for an overall period of 22 months. Ten months through November 2010 to August 2011 of observation was undertaken prior to, and twelve months following the introduction of the RCPC through September 2011 to August 2012.Although all available records were extracted from the Health Service Information System for the period from September 2011 to August 2012, there were gaps in the records available. The primary reason for these gaps was that many rural clinics were newly built or merged, there were no records collected during the reconstruction period. Accounting for these limitations, this study selected prescription records from a total of 123 rural clinics.All records were drawn from the patients’ medical electronic documentation, the primary data source. The data was subsequently coded by post-graduate students, and assisted by professors from Beijing Normal University, Treatment coding concentrated on accurately identifying drugs that were antibiotics for both oral and intravenous use intended for systemic use, and comprehensive lists  were applied to assist the coders.All the valid prescriptions prescribed during the period were taken into account in final statistical analyses. For the purpose of statistical evaluation, the percentage of encounters with an antibiotic prescribed(using antibiotic use as abbreviation), which was recommended by the WHO , was conThe effect of the RCPC program was evaluated by segmented regression analysis. The model this study uses a linear trend in the outcome within each segment. The specification of the linear regression model to be analyzed is as follows:β0 reflects the baseline level of the outcome, the antibiotic use at the beginning of the period (at time 0); β1 represents the change in the antibiotic use that is independent from the intervention, which is the structural trend; β2 captures the change in level of the outcome, representing the antibiotic use after the intervention; and β3 estimates the change in trend in the antibiotic use after the intervention [β4 controls for the Spring Festival holiday, which is a circumstantial event. It is when the Spring Festival that is the coldest time of the year in China, and common seasonal illness (cold) prevalence. The possibility of overuse antibiotics rises to treat fever and other associated symptom [cold is assigned the value 1 over the period and 0 otherwise. The error term εt at time t represents the random variability unexplained by the model. Linear regression model consists of a normally distributed random error and an error term at time t that may be correlated with errors at preceding or subsequent time points.In this model, rvention ; β4 cont symptom . The varεt, and εt = ρεt − 1 + μt,| ρ| < 1, where μt was the classical error term.All the tests consider the two-sided significance level of 5%. Stata version 12.0 was used to perform all statistical analyses including autocorrelation. Autocorrelation may lead to underestimated standard errors and overestimated significance of the effects of an intervention and the value of Durbin-Watson statistic close to 2 indicates sign of first-order autocorrelation. In this study, generalized difference method was employed. Assuming there was first-order autocorrelation with For equation , if alloρ, then equation  that were subject to the intervention is presented in Fig. 2 value of 0.83. A Durbin-Watson statistic of 1.923, larger than the upper value of 1.66 and around 2, suggests that results from Model 1 is without autocorrelation (see Table P = 0.480). With the intervention, it is estimated that there was no significant immediate change in the level of antibiotic use (P = 0.089), such that level of the series dropped by approximately 6.15% for an encounter with an antibiotic prescribed . While after the RCPC program, this rate had been reduced to 1.12% per month and this change in the underlying trend was statistically significant (P = 0.034).For antibiotic use, this regression adjusting for auto-correlation model was highly predictive, yielding a total RThis study applies interrupted time series data, using a pre-experimental study design to estimate intervention effects in nonrandomized settings, which is one of the strongest way to capture the effect of the intervention effectively . AlthougP = 0.089) when the RCPC was introduced, the RCPC program steeply reduced antibiotics prescription rates indeed which dropped significantly and rapidly by about 1.12% per month (P = 0.034). These findings strongly suggest that this program can reduce oral antibiotics and combined use of antibiotics and benefit the prescription practices of rural physicians. Examining relative changes in prescription rates prior to and following the intervention highlights the durability of the effect of the RCPC program.Analysis of the impact of the intervention demonstrated that both immediate and long term changes in the percentage of encounters with a prescribed antibiotic are associated with the RCPC program. As Fig. The RCPC program is designed to enhance rational drug prescribing practices by alternating rural physicians’ financial incentives from overprescribing and over-the-counter availability of antibiotics sales to prescription performance. Much of the damage caused by incorrectly prescribed antibiotics, including increased antibiotic resistance, unaffordable economic costs, and lack of compliance were prevented. Furthermore, to improve rural physicians prescribing practices, it strengthened rural clinic supervision, regulated medical practices, and effectively utilized various types of medical resources to identify potential medication problems and evaluate the appropriateness of clinical drug use . This peer review and feedback program initiative undertaken in Huangdao District improved physicians’ prescribing practices and promoted rural residents’ medical prescription and medication safety. It could be taken as a kind of comprehensive quality management of the medical services offered by rural clinics, which encourages continuous improvements in the quality of care, changing physicians’ prescribing practices. After released from the fee for service model, there are few over-prescriptions. The affordability and accessibility for rural residents to see doctors and receive medical treatment increases, and make “minor illnesses cured within the village, the general illnesses within the town, and serious illness within the city”.With respect to study limitations, in contrast to the general recommendation that 12 data points prior to, and 12 data points following the intervention should be used . In thisIn conclusion, this study demonstrated that use of a peer review and feedback policy in primary health care facilities could not only decreases the rate of encounters with prescribed antibiotics, but also improves prescribing behavior of general rural clinic physicians. These results will be substantial contributions to the effectiveness of treatments, safety of therapy and quality of health services.P = 0.034) in antibiotic use after its implementation in long term. Given the increasing antibiotic resistance worldwide, promoting regular prescription audit and feedback program in medical settings might help decline or prevent overprescribed antibiotic.This study provides evidence that that the prescription audit and feedback program was associated with significant decreases (


RD), initially misdiagnosed as Kimura's disease, with sustained good partial response in a 37‐year‐old male. To the best of our knowledge, this is the first reported case of radiation for extra‐orbital IgG4‐RD, albeit inadvertently.We describe the use of radiotherapy for parotid IgG4‐related disease (IgG4‐ IgG4‐related disease (IgG4‐RD) is a benign, chronic, multi‐organ disorder with fibro‐inflammatory infiltrate on histopathology, and heterogeneous clinical features depending on the site(s) of involvement. Its pathogenesis is uncertain, with both autoimmune and allergic characteristics. First described in 2003 by Kamisawa and Nakajima, the entity unifies many site‐specific diseases previously considered distinct . The onset is typically subacute with gradual development of tumour‐like masses detected on physical examination or on imaging, in the absence of systemic symptoms. It is characterised by elevated serum IgG4 levels and IgG4‐expressing plasma cells in affected tissues, but neither are specific. Instead, careful correlation of pathology, clinical, serologic and imaging findings is required to make the diagnosis, and confusion with other disease entities, including Kimura's disease (see below) is common. IgG4‐RD responds to many systemic agents, notably corticosteroids and other immunosuppressants , but relapse is frequent. More recently, targeted therapies such as the CD20 (B‐cell) monoclonal antibody rituximab, T‐cell‐depleting agents and also various immuno‐stimulatory antibodies have shown great promise.9/L (0.02–0.50). Fine needle aspiration cytology and subsequent skin punch biopsy in early 2010 had shown prominent eosinophil infiltrates including eosinophil micro‐abscess formation in association with lymphoid tissue, lymphoid follicles, proliferating post‐capillary venules and variable fibrosis. Plasma cells were present, although not dominant, and there was no storiform‐patterned fibrosis or phlebitis. Some vessels had hyaline thickened walls. No malignant transformation, granulomatous component, tissue parasites or significant neutrophil presence was identified  was 2.6 × 10Examination revealed a firm soft tissue mass in the left pre‐ and post‐auricular region Fig. . It measCT scan of the head demonstrated diffuse infiltration of the left peri‐auricular skin, subcutaneous soft tissues and parotid of maximum dimensions 90 × 90 × 35 mm but no other masses or lymphadenopathy . Repeat CT head/neck/chest/abdomen at that time (and previously in 2013), showed involvement of the parotid regions only. During follow‐up, he also had opinions from medical oncology, haematology, ENT and immunology specialists. Immunosuppressants were considered, but relatively contraindicated because of his history of Hepatitis B.The treatment course was uncomplicated. By 3 months, the mass had progressively shrunk to 25 × 15 mm, 3 mm proud  by his immunologist to commence cyclosporine 100 mg BD, in order to minimise the need for further courses of steroids. This led to rapid response of all disease sites. RT remains an option for the right parotid region (or elsewhere) if needed in the future.This case study demonstrates that intermediate dose RT can provide sustained local cosmetic benefit for parotid IgG4‐RD . It also demonstrates that interpretation of IgG4‐RD pathology can be challenging, particularly because histologic characteristics are heterogeneous at different sites. The chosen dose of 30 Gy in 15 fractions was based upon the original diagnosis of Kimura's disease, a benign inflammatory disorder of uncertain aetiology, possibly an aberrant immune reaction to an unknown antigenic stimulus. It is rare except in the Asian population, but sharing many histopathological features with IgG4‐RD which partly explains the diagnostic confusion here. There are anecdotes of Kimura's disease associated with a distant history of arthropod bite and, interestingly, this patient did report an insect bite on his left ear while working in the Burmese rice fields some years previously. Indeed, this was one of the features which led his referring dermatologist to the initial clinical diagnosis. Kimura's disease manifests with solitary or multiple subcutaneous nodules or masses often accompanied by regional lymphadenopathy and/or salivary gland hypertrophy, most commonly affecting the head and neck area, particularly the parotid and cervical regions. It typically presents in the third decade of life, with a marked male predominance. Systemically, there is usually marked eosinophilia and elevated serum immunoglobulin E (IgE) levels. The disease course can be chronic and relapsing and results in significant morbidity as the slowly enlarging masses become painful and locally infiltrative, but malignant transformation has not been observed. Histological examination characteristically reveals subcutaneous mixed inflammatory infiltrates including reactive lymphoid follicles and frequent eosinophils. Proliferating post‐capillary venules are lined by generally flattened endothelial cells, mast cells are increased whilst there may be eosinophil abscesses, eosinophil‐rich granulomas, follicular lysis, polykaryocytes, IgE expression and fibrosis in older lesions.RT has been used for Kimura's disease, reported doses ranging from 13 to 56 Gy, with no dose‐response beyond 26–30 Gy in conventional fractionation.potential option if needed, particularly for localised involvement.In summary, this case demonstrates that IgG4‐RD can constitute a clinical and pathological diagnostic dilemma, as none of the features are unique. The possibility needs to be entertained in the setting of slowly enlarging, histologically benign mass(es), particularly in the head and neck region. Similar to competing non‐malignant diagnoses such as Kimura's disease, IgG4‐RD is radio‐responsive. This was already known for orbital disease, but we have demonstrated radio‐sensitivity  also for IgG4‐RD of the parotid region. Given the availability of many systemic agents, and that RT for non‐malignant diseases should always be undertaken with caution, we are not advocating that RT be high on the list of treatment options for IgG4‐RD, rather that it is a This case study was approved by the Royal Adelaide Hospital Research Ethics Committee and the patient gave written informed consent.The authors declare no conflict of interest.


GAR+] prion-like elements partially relieve carbon catabolite repression in Saccharomyces cerevisiae. They have been hypothesized to contribute to wine yeast survival and alcohol level reduction, as well as communication with bacteria and stuck fermentation. In this work, we selected [GAR+] derivatives from several genetic backgrounds. They were characterized for phenotypic penetrance, heritability and confirmed as prion-like through curing by desiccation. In terms of fermentation kinetics, the impact of the prion on anaerobic wine fermentation  was either neutral or negative, depending on the genetic background. Likewise, residual sugars were higher or similar for [GAR+] as compared to the cognate [gar-] strains. The prions had little or no impact on glycerol and ethanol yields; while acetic acid yields experienced the highest variations between [GAR+] and [gar-] strains. Strains analyzed under aerobic conditions followed the same pattern, with either little or no impact on fermentation kinetics, ethanol or glycerol yield; and a clearer influence on volatile acidity. Although no clear winemaking advantages were found for [GAR+] strains in this work, they might eventually show interest for some combinations of genetic background or winemaking conditions, e.g., for reducing acetic acid yield under aerated fermentation.[ Saccharomyces cerevisiae is the main yeast species responsible for alcoholic fermentation of many traditional foods and beverages. It exhibits alcoholic fermentation even under aerobic conditions, making it an archetypical Crabtree-positive yeast. The Crabtree effect is characterized by low alcoholic fermentation until sugars are almost exhausted, although oxygen availability would allow for more efficient ATP production via respiration. In contrast, Crabtree-negative yeasts show respiratory metabolism under these conditions, producing almost exclusively carbon dioxide and biomass, and no ethanol. Several biological mechanisms contribute to the Crabtree effect, including carbon catabolite repression (CCR) of mitochondrial and respiration related genes  of [GAR+] induction in an evolutionary and ecological context. The nature of the inducing molecule is still controversial, since some authors found lactic acid , EC1118 , T73 , and UCD522 (maurivin) are commercial winemaking strains. IFI87 and IFI473 are strains from the collection of the ancient Instituto de Fermentaciones Industriales  and are currently deposited at the CECT collection as, respectively, CECT12512 and CECT12658. In addition, a [GAR+] derivative of the laboratory strain W3031A, together with its [gar-] counterpart, kindly provided by Daniel F. Jarosz, were used for reference purposes. Strains were routinely maintained on YPD plates , or as glycerol stocks (20% glycerol) at -80°C. GGM  was used as selective medium for prion isolation and phenotypic confirmation. YPGly  was used as permissive medium for the growth of both [gar-] and [GAR+] strains. Ingredients for culture media were of at least 99% purity, purchased from Sigma-Aldrich. Agar was purchased from Thermo Fisher (Oxoid).Six Vitis vinifera L. cv. Viura) from the 2017 harvest , containing about 100 g/L glucose, 98 g/L fructose, pH 3.6. It was stored in frozen aliquots (-20°C). Before use, in order to reduce microbial load, it was thawed and submitted to thermal treatment by heating in an autoclave until reaching 105°C; and then, immediately, stopping heating and allowing the autoclave to cool down.Fermentation experiments were run in either Falcon tubes or MiniBio Bioreactors . Pre-cultures were grown in YPD  for 48 h at 25°C. All experiments were run in triplicate and three independent inocula were prepared for each strain and culture condition. Fermentation medium was a natural white grape must  containing 20 mL of grape must and closed with fermentation locks . Fermentation kinetics was monitored by daily recording weight loss. Fermentations were incubated at 25°C (static) and stopped after 10 days. By the end of the experiment, cultures were centrifuged and fermentation metabolites in the supernatant analyzed by HPLC.Yeast cells were grown on YPD for 48 h at 25°C; then washed with the same volume of distilled water and used as inocula for fermentation assays. Small volume fermentations, inoculated at a final OD600 of 0.2 (with inocula prepared as described above). They were sparged with dry air or nitrogen, for aerobic or anaerobic conditions, respectively. Flow of the input gas was adjusted to 25 mL/min with MFC17 mass flow controllers  whose calibration was regularly verified with an electronic flowmeter . CO2 content in the output gas flow was recorded every 60 s with the aid of BlueInOne Cell gas analysers  connected to each bioreactor. Stirrer was set at 1000 rpm and temperature at 25°C.Fermentations in laboratory scale bioreactors , were performed with the same batch of natural grape must as above, with 150 mL working volume. Cultures were inoculated at a final OD2SO4 as mobile phase, at 0.6 mL/min. Prior to injection, samples were filtered through 0.22-μm-pore-size nylon filters and diluted 10-fold.Concentration of the main metabolites, glucose, fructose, glycerol, acetic acid and ethanol, was determined in duplicate for each sample, by HPLC, using a Surveyor Plus chromatograph  equipped with a refraction index and a photodiode array detector . HI-Plex H 300 mm × 7.7 mm column and guard (Agilent Technologies) were used and maintained at 50°C. Elution was performed with 1.5 mM HGAR+] strains were recovered according to 600. Serial (1/10) dilutions were prepared on 96-well microplates, with a multichannel automatic pipette, and used to inoculate rectangular agar plates (GGM) with a manual 96-pin replica plater. Control plates were inoculated in parallel from the same yeast cell dilutions.Putative [GAR+] cells were grown on YPD until constant OD (about 4 days). The cultures were washed on the same volume of diluted PBS (1:80) and distributed in screw cap microcentrifuge tubes (2 mL per tube), centrifuged again and the supernatant carefully removed. For initial values of penetrance and heritability, this pellet was immediately suspended in water and dilutions prepared for further analysis. For the impact of desiccation, pellets were incubated at 25°C for up to 10 weeks. For each time point one tube from each strain was suspended in water and used for penetrance and heritability quantification.Phenotypic penetrance and heritability were studied in association with the analysis of the impact of desiccation. The assay was based on the method described by GAR+] strain in selective versus permissive medium (GGM vs. YPGly). These plates were inoculated with suitable dilutions of the cell suspensions prepared as described above, and plates containing 50–300 colonies counted after 3–7 days, depending on the genetic background and the culture medium. For the quantification of heritability, 10 single colonies from permissive medium were checked for prion status as described in the previous section. Heritability was calculated as the fraction of colonies retaining the [GAR+] phenotype.Penetrance of prions on each genetic background was quantified as the ratio between colony counts for each  on winemaking the first step was to obtain wine yeast strains carrying this prion-like element. Six different genetic backgrounds (as well as W303 strain as a reference) were used for this purpose. [GAR+] strains were identified as described in Section “Materials and Methods” and by GAR+] derivative. Most of them were also able to use raffinose or maltose in the presence of glucosamine but were not derepressed for the use of glycerol in the presence of 2-deoxy-glucose (data not shown). This indicates the CCR loosening under the prion state being, at most, incomplete with some glucose repression pathways still active.In order to study the relevance of [GAR+] prion-like elements in the wine making process would be phenotypic penetrance. The first trial to confirm the prion state of these strains was based on the expectation that plating [GAR+] strains in parallel in selective and permissive medium would result in similar colony counts. However, colony counts in selective medium fell far below those in the control medium. Indeed, despite penetrance was not analyzed in the original descriptions of [GAR+] .An important feature to consider toward understanding the relevance of [f [GAR+] ,b, low pf [GAR+] . We there Figure . T73[GARGAR+] epigenetic elements distinguishing them from classical, nucleic acid based, genetic determinants  is another key feature of  and [GAR+] strains of each one of the six industrial genetic backgrounds. In three cases, viz., EC1118, FX10, and IFI473, the fermentation profiles of the original strains and those harboring the prion were indistinguishable  to clearly impaired (T73 and UCD522) fermentation kinetics; with weight losses for the prion strain 30% or 115% below the control strain by the 5th day of fermentation. It is worth noting the strong effect of the prion state in the T73 background despite the low penetrance described above. This would indicate that phenotypic penetrance on the plate assay is not fully related with the prion behavior under different culture conditions. In agreement with these fermentation profiles, residual sugar by the end of fermentation was either similar or increased for most strains under the prion state  was especially striking in the T73 background , comparing the . Considering previous reports that relate the [GAR+] epigenetic element with reduced ethanol yield . Aerobic cultures on the FX10 background were also arrested before complete sugar consumption, but the difference between both strains (prion or not) was almost negligible.Sugar consumption profiles during the first 2 days of fermentation faithfully mirrored the trends observed for COGAR+] element along the fermentation time  than for its [gar-] counterpart (15 mg/g)  Figure .GAR+] elements on the fermentative behavior and the yield of main fermentation metabolites for six different wine yeast strains. Strains carrying this epigenetic element were selected as described by bona fide [GAR+] strains, apart from the ability to readily grow on GGM plates . These include, frequency of isolation  on ethanol content, and apparently no impact on ethanol yield, since in that case reduced ethanol content was concurrent with a comparable increase in residual sugar. Our results, starting with six different wine yeast strains, point to the same direction as S. cerevisiae cultures under standard fermentation conditions.One feature of  prions.In addition, one strategy to lower ethanol levels in wine that is currently under research is based on respiratory metabolism . Since CGAR+] prion, either under aerobic or anaerobic conditions. Acetic acid yield was especially interesting because its production was previously identified as a major drawback when using S. cerevisiae to reduce ethanol content by respiration .RG, PM, and KP conceived and designed the study. LL-B, AM, CJ, AR, JC, JT, NG, MF-P, and AO performed the experiments. RG, PM, AM, LL-B, and CJ analyzed the data. RG, KP, PJ, PM, and JT interpreted the results. RG, KP, and PJ wrote the manuscript. All authors discussed and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Understanding community perspectives on antibiotics and antibiotic resistance (ABR) is a key component in designing educational interventions to combat ABR at the community level in Malaysia. Therefore, this study aimed to explore community residents’ knowledge, attitudes and perceptions regarding antibiotics and ABR in Jelutong District, Penang, Malaysia. Moreover, it intended to identify areas of focus to be addressed when designing an educational intervention to increase residents’ knowledge and change their attitudes and perceptions.A qualitative approach was adopted to gain a deeper understanding of community residents’ knowledge, attitudes and perceptions regarding antibiotics and ABR. A purposive sampling was employed. Twenty-two residents (aged ≥18 years) were interviewed with the aid of a semi-structured interview guide. All interviews were audio recorded, transcribed verbatim and thematically analysed.The majority of the participants asserted that antibiotics could be effective against viral infections. Moreover, many participants were unaware that antibiotics have adverse effects. Some acquired antibiotics from a community pharmacy without a prescription, took antibiotics given to them by their family or friends, or took leftover antibiotics prescribed for a previous illness. A few indicated that they would request antibiotics from their physician when they had viral infections. More than half of the participants discontinued taking antibiotics when their symptoms improved. The majority stated that ABR occurs when the body becomes used to antibiotics. Most participants were unaware of the causes, consequences and prevention of ABR. In fact, they were not concerned about it. As a result, only a few perceived themselves as having responsibility for preventing this problem.The community residents had misconceptions about antibiotics and ABR, negative attitudes towards antibiotics and negative perceptions of ABR. The areas of focus that need to be addressed when designing an educational intervention to increase the general public knowledge and change their attitudes and perceptions are the appropriate use of antibiotics and their adverse effects; the importance of adhering to antibiotic therapy; and the definition, causes, consequences and prevention of ABR. Antibiotic resistance (ABR) is a global public health problem that threatens the treatment and prevention of bacterial infections and undermines advanced medical procedures such as cancer chemotherapy, organ transplantations and surgeries –3. ABR cThe World Health Organization (WHO), concerned with this growing threat, has developed a global action plan for ABR and urges all nations to increase public knowledge of antibiotics and ABR through effective education and communication . To desiBased on an extensive search of the literature using several electronic databases , there is a paucity of data regarding community residents’ knowledge, attitudes and perceptions in relation to antibiotics and ABR in Malaysia. Moreover, it is inappropriate to extrapolate the findings from public attitudes and perceptions conducted in other countries to the local situation because of differences in healthcare systems, contexts and cultures . TherefoA qualitative phenomenological approach was employed in this study because it allows the researchers greater freedom in exploring participants’ knowledge, attitudes and perceptions regarding antibiotics and ABR –36. In aThis study was conducted at 1Malaysia Community in Makloom Street, Jelutong between 4 October and 6 December 2016. Jelutong is an urban district located in North-east Penang. The total number of 1Malaysia Community residents (aged ≥18 years) was approximately 1200 in 2016 . The resThe study site (i.e. population) was selected based on several factors. First, the School of Pharmaceutical Sciences, Universiti Sains Malaysia (USM) has good rapport with 1Malaysia Community in Makloom Street. This helped the authors gain access to the field. Second, the community residents showed an interest in the research topic and supported the study. Third, the residents are from different age groups and ethnic, educational and socioeconomic backgrounds. This offered the authors the opportunity to gain a heterogeneous sample. Finally, there was no pre-established relationship between the authors and the participants prior to the study commencing. Thus, participants’ responses would not be distorted and any pre-conceptions would be eliminated from the authors’ understanding of the study phenomena.Participants were included in the study if they were residents of 1Malaysia Community; were 18 years of age and over; were aware of the term ‘antibiotics’; and were able to speak, read and write in English or Malay. Healthcare professionals, those who did not meet the inclusion criteria or those unwilling to participate were excluded from the study.Purposive sampling was adopted in the study because it is the primary sampling technique used in qualitative studies –44. In aBefore the data collection began, the first author (LI) met the leader of 1Malaysia Community to inform him of the study, seek his endorsement and discuss any concerns. Since the first author did not know any of the community residents prior to the study commencing, she requested the community leader to nominate those who fulfilled all the study criteria and had the potential to provide rich and relevant data –49.The interviewer (LI) met the nominees and provided them with verbal and written information about the study. Those who agreed to participate were asked to contact the interviewer to arrange an interview. The recruitment continued until data saturation was achieved –53, as iA semi-structured interview guide  were conducted in English and the other half (n = 11) were conducted in Malay. As the relationship with the participants had not yet been established, the interviewer began the interviews by introducing herself and asking some introductory questions to build a rapport with them. The interviews focused on participants’ knowledge, attitudes and perceptions regarding antibiotics and ABR. Appropriate probing questions were asked when necessary. To extricate further ideas from the participants, they were given the freedom to express additional opinions on antibiotics and ABR at the end of the interviews. The interviews were held in 1Malaysia Community hall at a time convenient for the participants. Each interview lasted between 30 and 40 min. Field notes were made during and after each interview. None of the interviews were repeated.Prior to the interviews, written informed consent was sought and the participants were asked to complete a demographic survey concerning their age, gender, ethnicity, marital status, education level, employment status, monthly household income, the last time they had taken antibiotics and the number of antibiotic courses they had taken in the previous year. Afterwards the interviewer, who is experienced in conducting qualitative interviews and is well-versed in English and Malay, conducted the face-to-face, semi-structured interviews with the aid of the interview guide. Based on the participants’ preference, half of the interviews (n = 11) were then translated into English for analysis.All interviews were audio recorded using a digital voice recorder with the participants’ consent. The recordings were then anonymised and transcribed verbatim by a professional transcriber who is familiar with medical terminology and fluent in English and Malay. The interviewer checked all the transcripts against the audio recordings for accuracy and completeness. When necessary, amendments were made, and then a copy of the transcript was returned to the interviewed participant for verification. All participants endorsed the transcripts without making any corrections. The Malay transcripts (n = 22) were thematically analysed by the first author (LI) and an independent researcher with expertise in qualitative research. The analysis began with data familiarisation, a process that involved reading the transcripts repeatedly and noting down ideas. Subsequently, the information pertinent to participants’ knowledge, attitudes and perceptions regarding antibiotics and ABR was identified and coded based on deductive and inductive approaches. These codes were then collated into themes and sub-themes. The first author subsequently discussed the coding, themes and sub-themes with the independent researcher to enhance the data reliability. Afterwards they were reviewed by the co-authors . Any discrepancies were resolved by discussion until a consensus was reached. The first author was then presented the findings to the study participants and obtained their feedback to ensure that their perspectives were accurately and clearly represented.All English transcripts (n = 12) were females. The ages of all participants ranged from 18 to 70 years (Median [Q1-Q3] = 48  = 48 –64). The–P22 wereFour major themes were identified: knowledge of antibiotics; attitudes towards antibiotics; knowledge of ABR; and perceptions of taking responsibility for combating ABR Table .Table 2To explore participants’ knowledge of antibiotics, the interviewer asked them about their understanding of the term ‘antibiotics’ and antibiotic use. The interviewer also asked participants about the adverse effects of antibiotics.‘Antibiotics are medicines that kill viruses. They are medicines used to speed up recovery from colds and coughs.’ (P7)‘Antibiotics are medicines that kill small living things called viruses. They can cure colds and sore throats quickly.’ (P11)The participants had different understandings of the term ‘antibiotics’ and antibiotic use. The majority had a misconception that antibiotics are medicines that kill viruses and can hasten recovery from viral infections:‘As far as I’m concerned, antibiotics are medicines that bring down a high temperature.’ (P2)‘All I know is that antibiotics are medicines used to reduce fevers.’ (P22)Some participants understood antibiotics as medicines that reduce fevers:‘I’m completely certain that antibiotics are medicines that ease pain and swelling.’ (P3)‘To my knowledge, antibiotics are the same as painkillers. They reduce pain and swelling.’ (P21)A few participants understood antibiotics as medicines that relieve pain and reduce inflammation:‘Antibiotics are medicines that kill germs called bacria [bacteria]. They are effective for the treatment of bacria [bacterial] infections such as umonia [pneumonia].’ (P1)‘Antibiotics are medicines that kill bacteria. They can be used to treat skin infections and urine [urinary tract] infections.’ (P15)Two participants stated that antibiotics are medicines that kill bacteria and can be used to treat bacterial infections:‘Antibiotics are pills that prevent all kinds of illnesses from getting worse.’ (P9)One participant indicated that antibiotics are medicines that prevent any illnesses from becoming severe:‘I really don’t know whether or not antibiotics have side effects. I’ve never experienced any of them.’ (P2)‘I’m not sure if antibiotics can cause side effects. I have never had side effects from the medicine.’ (P7)Most participants were unaware that antibiotics have adverse effects; none had experienced adverse effects while taking antibiotics:‘As far as I’m concerned, antibiotics can cause side effects such as stomach discomfort. If I experience any side effects, I would go back to my doctor.’ (P14)‘Yes, antibiotics have side effects. If I’m not mistaken, they can cause diarrhoea and rashes. If that happens, I would return to my doctor.’ (P17)Only a few participants were aware of some adverse effects of antibiotics such as diarrhoea, stomach discomfort and rashes. They stated that they would seek further consultation with their physician if adverse effects occurred:To explore participants’ attitudes towards antibiotics, the interviewer asked them how they acquired antibiotics. Participants were also asked about their responses to physicians’ decisions to prescribe antibiotics and their adherence to antibiotic therapy.‘I never request antibiotics from my doctor. He prescribes them and advises me how to take the medicine.’ (P12)‘My doctor prescribes me antibiotics and advises me how to take them.’ (P22)The majority of participants reported that they acquired antibiotics from a physician and were advised how to take them:‘When I have a cold, I buy antibiotics in a [community] pharmacy without a prescription because they help me get better. If there is no improvement after taking them, I’ll see a doctor.’ (P7)‘When I have a sore throat, I go to a [community] pharmacy and ask for antibiotics as I want to get better quickly. If my condition doesn’t improve after taking them, I’ll see a doctor for advice.’ (P10)Some participants acquired antibiotics from a community pharmacy before consulting a physician, as they wanted to recover quickly from viral infections. They said that they would consult the physician if symptoms persisted:‘I take an antibiotic given by my mum. She said the medicine is effective against colds. I try it and it works.’ (P4)‘When my throat is a bit painful, my girlfriend gives me antibiotics. She said they are good for sore throats. I believe what she said and take the medicine according to her advice.’ (P11)A few participants took antibiotics given to them by their family or friends, as they believed that antibiotics are effective for treating colds and sore throats:‘If I have similar symptoms, I don’t want to see a doctor because of a long wait in the clinic. I would rather take leftover antibiotics prescribed for my past illness.’ (P8)‘When I have the same symptoms, I usually take leftover antibiotics prescribed for my previous illness. I can’t stand the long waiting time in the clinic.’ (P16)Two participants indicated that they took leftover antibiotics prescribed for a previous illness when similar symptoms arose, as they wanted to save the time it would take to visit a primary-care clinic:‘I trust my doctor. If she doesn’t prescribe antibiotics, I won’t ask for such medicines. I’ll take any medicines given by her.’ (P5)‘I have confidence in my doctor. Whether or not he prescribes antibiotics, I’ll abide by his decision. I won’t demand antibiotics.’ (P19)When asked about their responses to physicians’ decisions to prescribe antibiotics, the majority stated that they would abide by their physician’s decisions and would not request antibiotics, as they trust the physician:‘Although I want antibiotics, I don’t dare to ask my doctor to prescribe the medicine. I would rather build a good relationship with the doctor.’ (P2)‘Deep down, I wish to take antibiotics when I’m not feeling well. But, if my doctor doesn’t prescribe the medicine, I won’t request them. I prefer to have a good relationship with the doctor.’ (P9)Some participants stated that they would not express their expectations openly to their physician nor request antibiotics, as they wanted to establish a good relationship with the physician:‘If I have a cold or sore throat, I’ll certainly expect antibiotics from my doctor as the medicine will help me get over it faster. If he refuses to prescribe antibiotics, I’ll see another doctor.’ (P4)‘When I have a cold, I ask my doctor to prescribe antibiotics because I want to get well quickly. If he is reluctant to do so, I’ll consult another doctor.’ (P11)A few participants indicated that they would make their expectations explicit and request antibiotics from their physician when they had viral infections, as they believed the medicine promotes rapid recovery. They also said that they would consult another physician if their request was not granted:‘I follow the instructions on the label. But, I stop taking the antibiotics when I feel better. Why should I finish the prescribed course when I have recovered from the infection? I don’t understand!’ (P7)‘I take antibiotics according to the instructions on the label. But, I stop taking them when I feel better. Honestly, I don’t see the point why I should take the full prescribed course when symptoms have cleared up.’ (P16)When asked about how they took antibiotics, more than half of the participants stated that they adhered to antibiotic regimens. However, they discontinued taking the antibiotics when their symptoms improved, as they were unaware of the importance of taking the full prescribed course. They believed that they had recovered from the infection when they felt better:‘I occasionally miss one or two doses of antibiotics as I am busy with many things, but I always complete the prescribed course. If I miss a dose, I take the missed dose as soon as I remember, and then continue with the regular [dosage] schedule. I never take a double dose to compensate for the missed dose.’ (P2)‘I try my best to follow the instructions on the label. But, sometimes I forget to take one or two doses because I have a very busy life. If I miss a dose and it is almost time for the next dose, I skip the missed dose and then continue with the regular [dosage] schedule until I finish them all. I never take a double dose to make up for the missed dose.’ (P19)Some participants reported that they occasionally missed a few doses of antibiotics because of their hectic lifestyle. Nevertheless, they were aware of what they should do if they missed a dose and completed the prescribed course:‘I take antibiotics according to the doctor’s instructions and finish the prescribed course. Hopefully, all bacteria are killed.’ (P15)‘I follow the doctor’s instructions on how to take antibiotics. I finish them all, even if I feel better because I want to make sure all bacteria are killed.’ (P18)Only a few participants stated that they adhered to antibiotic regimens and completed the prescribed course to ensure that all bacteria had been killed:‘I put the leftover antibiotics in a drawer until a later clear out. When I’m free, I throw them away in a dustbin. I won’t take them at a later date.’ (P13)‘I keep the leftover antibiotics in a cabinet, but I won’t take them next time I’m not well. Eventually I’ll throw them out in a rubbish bin.’ (P21)Those who did not complete the prescribed course were asked what they would do with the leftover antibiotics. Most participants indicated that they kept them in a cupboard and eventually disposed them of in a dustbin; they had no intention of saving them for future use:‘I keep the leftover antibiotics and take them now and then when I have similar symptoms.’ (P8)‘I keep the leftover antibiotics in a cupboard and use them in the future.’ (P16)Two participants reported that they did keep the leftover antibiotics for future use:To explore participants’ knowledge of ABR, the researcher asked them about their understanding of the term ‘ABR’ and its causes, consequences and prevention.‘In my opinion, antibiotic resistance occurs when bacteria are able to resist the effects of antibiotics.’ (P1)‘As far as I’m concerned, antibiotic resistance is a condition where bacteria are able to protect themselves from the effects of antibiotics.’ (P5)Most participants had heard of the term ‘ABR’, but only two understood it as a condition where bacteria become resistant to antibiotics:‘Antibiotic resistance? What’s that? I don’t have a clue!’ (P4)‘Huh? This is the first I’ve heard of the term [antibiotic] resistance.’ (P10)‘What? I’m not aware of the term [antibiotic] resistance.’ (P22)Three participants were unaware of the term:‘Antibiotic resistance is a condition where the body becomes used to antibiotics.’ (P6)‘My understanding of antibiotic resistance is that it occurs when the body gets used to antibiotics.’ (P8)The majority stated that ABR occurs when the body becomes used to antibiotics:antibiotics losing their potency before killing bacteria:Other participants understood ABR as follows:‘I think antibiotic resistance occurs when antibiotics lose their potency before killing bacteria.’ (P21)the body becoming incompatible with antibiotics:‘The body is not compatible with antibiotics. That’s what antibiotic resistance is.’ (P13)the illness becoming too strong for antibiotics to manage:‘As far as I know, antibiotic resistance is a condition where an illness is becoming stronger than antibiotics.’ (P16)a hereditary illness:‘Based on my understanding, antibiotic resistance is a hereditary illness. If none of our family members is affected by antibiotic resistance, we won’t suffer from it.’ (P19)‘I guess there is a link between antibiotic use and antibiotic resistance. But, I’m not sure how antibiotic resistance arises.’ (P3)‘I don’t really know the root of antibiotic resistance. Perhaps there is a connection between antibiotic use and [antibiotic] resistance.’ (P6)Although most participants noted an association between antibiotic use and ABR, they expressed uncertainty about the causes of ABR:‘In my opinion, unnecessary antibiotic prescriptions can contribute to antibiotic resistance.’ (P12)‘I guess over-prescription of antibiotics can lead to antibiotic resistance.’ (P14)Some participants stated that inappropriate prescribing of antibiotics, including unnecessary prescription of this medicine, can lead to ABR:‘I think antibiotic resistance is likely to occur if we don’t take antibiotics according to the instructions on the label.’ (P15)‘Antibiotic resistance may occur if we don’t finish the prescribed course of antibiotics.’ (P18)A few participants attributed ABR to the irresponsible use of antibiotics such as not adhering to antibiotic regimens and not completing the prescribed course:‘When I picked up my dad’s medication from a [community] pharmacy, I saw something was not right. The pharmacist sold antibiotics under the counter. You know, such actions can lead to antibiotic resistance.’ (P17)‘I notice some [community] pharmacists sell antibiotics without a prescription, even though the law says otherwise. I think such things can contribute to antibiotic resistance.’ (P20)Two participants indicated that inadequately implementing the regulations on antibiotic availability could contribute to ABR. They reported that some community pharmacists dispensed antibiotics over the counter (OTC), although in Malaysia, regulations prohibit dispensing antibiotics without a prescription:‘I don’t know the consequences of antibiotic resistance. Anyway, it doesn’t concern me at all!’ (P10)‘I can’t think of the consequences of [antibiotic] resistance. In fact, I’m not concerned about it.’ (P13)Most participants were unaware of the consequences of ABR. Moreover, they were not concerned about it:‘As far as I know, illnesses are harder to treat because of [antibiotic] resistance.’ (P1)‘I’m sure the cost of treatment will increase because of antibiotic resistance.’ (P5)Only two participants were aware of some consequences of ABR, including infections being more difficult to treat and the higher cost of treatment:‘I’m just an ordinary person. I’m not sure how antibiotic resistance can be prevented. I guess there is nothing I can do about it. Anyway, I don’t think antibiotic resistance will affect me.’ (P2)‘I don’t know how we can prevent antibiotic resistance. I guess I can do nothing to slow down the spread of the resistance. Somehow, I believe that I’m not at risk of getting an antibiotic-resistant infection.’ (P6)Most participants were unaware of how ABR can be prevented. They also indicated that they were not at risk of contracting antibiotic-resistant infections and had a limited role in avoiding the emergence and spread of ABR:‘I suppose taking antibiotics exactly as your doctor tells you can prevent antibiotic resistance.’ (P15)‘Finishing the prescribed course of antibiotics can prevent antibiotic resistance.’ (P18)Conversely, only a few participants stated that responsible use of antibiotics, such as adhering to antibiotic regimens and completing the prescribed course, can prevent ABR:‘In my view, doctors should prescribe antibiotics when patients really need them. Besides, they should explain what we should do to prevent [antibiotic] resistance.’ (P12)‘In my opinion, doctors should give advice on how we can prevent antibiotic resistance. Most importantly, they should only prescribe antibiotics when patients need them.’ (P14)Other participants had some suggestions about how physicians, pharmacists and policymakers should prevent ABR. A few proposed that physicians should only prescribe antibiotics when they are needed, and should educate patients about ways to prevent ABR:‘I suppose the government should enforce the law so that antibiotics won’t be freely available in [community] pharmacies.’ (P17)‘The government should do something so that doctors won’t simply prescribe antibiotics and [community] pharmacists stop selling the medicine without a prescription.’ (P20)Two participants pointed out that policymakers should take steps to enforce the law on prescribing and dispensing antibiotics:‘Pharmacists should provide an adequate explanation of how to take antibiotics appropriately and how to avoid [antibiotic] resistance.’ (P19)Only one participant stated that pharmacists should educate patients on how to use antibiotics responsibly to prevent ABR:‘Apart from being trained in medical science, doctors are also qualified to prescribe antibiotics. Hence, they should take responsibility for combating antibiotic resistance.’ (P5)‘In my view, doctors play a key role in combating antibiotic resistance because they are experts in the field.’ (P8)When asked about the stakeholders who should take responsibility for combating ABR, the majority felt that physicians play a vital role in combating this major public health problem, as they are medical experts and have the authority to prescribe antibiotics:‘Pharmacists are part of the medical team. Their job is to prepare all sorts of medicines including antibiotics. So they should take responsibility for combating antibiotic resistance.’ (P3)‘As pharmacists prepare medicines for patients, there is no doubt in my mind that they should take responsibility for combating antibiotic resistance.’ (P9)Some participants indicated that pharmacists should also take responsibility for combating ABR, because they are members of the healthcare team and dispense medicines:‘As a consumer, I get the feeling that I could be affected by antibiotic resistance. Therefore, I should take action to prevent this problem.’ (P15)‘I think all patients, including myself, have responsibility for combating [antibiotic] resistance because all of us are at risk of getting an antibiotic-resistant infection.’ (P18)Only a few participants perceived themselves as having responsibility for preventing ABR, because they believed that they were at risk of contracting antibiotic-resistant infections:‘First and foremost, the government develops policies and has the power to enforce the law. Consequently, it plays a major role in combating antibiotic resistance.’ (P17)‘The government is the one who develops policies and therefore it has to take the lead in combating antibiotic resistance.’ (P20)Two participants emphasised that policymakers play a key role in combating ABR, as they develop policies and enforce the law:This qualitative study yields important findings regarding community residents’ knowledge, attitudes and perceptions in relation to antibiotics and ABR. It also identifies areas of focus that need to be addressed when developing an educational intervention to increase their knowledge and change their attitudes and perceptions.The study revealed that only a few participants were aware that antibiotics are medicines used to treat bacterial infections. The majority asserted that antibiotics are effective for treating viral infections, while others understood them as medicines that reduce fevers and inflammation, relieve pain, or prevent any illnesses from becoming severe. This aligns with the findings of other Malaysian studies, whereby the majority of the public surveyed in the States of Selangor (68%)  and PenaThis could be attributed to several factors. First, the study participants might not be adequately informed by healthcare professionals about what antibiotics should be used for and when they should be used . Second,This study revealed that most participants were unaware of the common adverse effects of antibiotics, while other Malaysian studies showed that slightly more than half of the public surveyed in Penang (54%)  and the Most of the study participants acquired antibiotics from their physician. This could be due to the fact that in Malaysia, most medicines are available free of charge in public hospitals and primary-care clinics , 82. PriThe WHO  suggestsThis study revealed that some participants occasionally missed a few doses of antibiotics because of their hectic lifestyle. Forgetting to take antibiotics indicates that participants had forgotten that they were feeling unwell or believed their condition was not severe, meaning that antibiotics were not needed or their condition had improved to the point that it was no longer necessary to take antibiotics , 110.Most of the study participants disposed of leftover antibiotics in a dustbin; none returned them to pharmacists or physicians. This aligns with the findings of other Malaysian studies, whereby the majority of the public surveyed in Kuala Lumpur (79%)  and PahaThe study revealed that most participants had heard of the term ‘ABR’, but only a few correctly understood the term as a condition where bacteria become resistant to antibiotics. The majority understood the term as the body becoming used to antibiotics, whereas others understood it as antibiotics losing their potency before killing bacteria, the body becoming incompatible with antibiotics, the illness becoming too strong for antibiotics to manage or a hereditary illness. This is consistent with the findings of qualitative studies carried out in European countries , India  and the Although most of the study participants were aware of a correlation between antibiotic use and ABR, they remained uncertain about the causes of this problem. Some attributed ABR to external factors, such as inappropriate prescribing or dispensing of antibiotics without a prescription, rather than internal factors, such as non-adherence to antibiotic therapy. In addition, they believed that they were not at risk of contracting antibiotic-resistant infections, despite the fact that antibiotic-resistant bacteria can spread readily from one person to another and affect anyone , 120. AsThe study showed that most participants were unaware of the consequences of ABR, and not concerned about this issue. Similar findings have been reported in the UK , 27, wheThe purposive and maximum variation sampling was employed in this study. In fact, this sampling strategy can achieve representativeness and capture the heterogeneity in the population. Thus, the study managed to capture a wide range of community residents’ views, knowledge, attitudes and perceptions regarding antibiotics and ABR. Hence, it provided a greater insight into the study phenomena . In addiThe findings indicate that the majority of community residents lacked knowledge about antibiotics and ABR, had negative attitudes towards antibiotics and had negative perceptions of ABR. Therefore, there is an urgent need to develop and implement educational interventions to address key gaps in their knowledge, correct common misconceptions and shift their attitudes and perceptions. The areas of focus that need to be addressed include the appropriate use of antibiotics and their adverse effects; the importance of adhering to antibiotic therapy; and the definition, causes, consequences and prevention of ABR.Additional file 1. Interview guide


Seasonal variation has been observed for various bacterial and viral infections. We aimed to further study seasonality of respiratory viruses and bacterial pathogens in relation to antibiotic use, as well as meteorological parameters.Clostridioides difficile, Methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pneumoniae, and Escherichia coli and Klebsiella pneumoniae  in Rhode Island from 2012 to 2016.An ecologic study of antibiotic exposure, meteorological parameters, detection of respiratory viruses  and clinical isolates of C. difficile occurred 3 months after the peak in antibiotic prescriptions filled . Peak MRSA detection was noted 7 months after the peak in antibiotic prescriptions filled  and 10 months after the peak in respiratory virus detection . Peak GNB detection was noted 2 months after the peak mean monthly ambient temperature . Peak detection of S. pneumoniae was noted at the same time as the peak in detection of respiratory viruses .Peak detection of C. difficile seasonality may, in part, be related to antibiotic prescriptions filled; GNB seasonality may be related to ambient temperature and S. pneumoniae may be related to concurrent respiratory viral infections.We identified distinct seasonal variation in detection of respiratory viruses and bacterial pathogens. The online version of this article (10.1186/s13756-019-0574-7) contains supplementary material, which is available to authorized users. Clostridioides difficile infection is temporally associated with respiratory tract infections [Many host-related risk factors have been established for bacterial infections; however, non-intrinsic factors such as respiratory viral infections, weather conditions, and latitude are among other factors that lead to seasonality of such infections –6. In adfections , likely A better understanding of seasonality of various pathogens, as well as an association with antibiotic prescriptions may allow us to devise and implement future public health interventions , particularly in the community setting. The purpose of this study was to assess seasonality of respiratory viruses and bacterial pathogens in relation to antibiotic use and meteorological parameters in one locale.This was an ecological study involving detection of bacterial pathogens and respiratory viruses in Rhode Island. Microbiologic data included specimens sent to the Lifespan Microbiology Laboratory from inpatients and outpatients assessed in the  Lifespan healthcare system . The system is licensed for 1,165 beds, with 62,100 patient discharges, 257,081 emergency department visits, and 757,380 outpatient visits , as wellClostridioides difficile toxin was identified by PCR testing of stool specimens ; growth in clinical cultures identified cases involving Methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pneumoniae, and Escherichia coli and Klebsiella pneumoniae . Only the first encounter with one of the above-noted pathogens was included if a patient had multiple episodes of positive laboratory testing for that pathogen within 30 days. We excluded MRSA identified only from nares screening. Incidence reflected counts with no denominator based on the assumption that there was no significant year-to-year variability between practices in obtaining respiratory specimens  was queried to find positive microbiology laboratory identification of respiratory viruses identified by the respiratory viral panel , rapid influenza test  or rapid Respiratory Syncytial Virus test  from an outpatient’s or inpatient’s nasopharyngeal swab or bronchoscopic lavage specimen. The target population included all ages regardless of insurance status. The respiratory viral panel included testing for Influenza A/B, respiratory syncytial virus (RSV) A/B, Coronavirus, Parainfluenza virus, human Metapneumovirus, Adenovirus, Rhinovirus/Enterovirus (the panel does not differentiate Rhinovirus and Enterovirus). Antibiotic prescription data from January 2012 through December 2016 was used to assess antibiotic exposure. Data was obtained from the Rhode Island All Payer Claim Database (ACPD), provided by Rhode Island Department of Health. The ACPD collects and stores payer enrollment data, medical claims, pharmacy claims, and provider data on a monthly basis from commercial insurers, Medicare and Medicaid regarding antibiotic prescriptions filled . The denMonthly aggregated data on average temperature and total precipitation from January 2012 through December 2016 in Rhode Island was retrieved from the National Centers for Environmental Information [C. difficile, MRSA, GNB, and S. pneumoniae)  with 95% confidence intervals, estimating risk of elevated incidence compared to annual average incidence. Due to the small numbers and multiple testing, the p-values should only be seen as descriptive measures. Analyses were performed using R . Packages used were: forecast, TSA  [The null hypothesis was no seasonal cross-correlation between respiratory viral activity, antibiotic prescriptions filled, weather variables and detection of different bacterial pathogens. We constructed a longitudinal incidence rate using a monthly dataset which included respiratory viruses detected, antibiotic prescriptions filled, and meteorological parameters , as well as detected bacterial pathogens (ae) Fig. . A seasonalysis) , and ASTnalysis) .Fig. 1ScC. difficile, 4,026 MRSA, 9,767 GNB, and 272 S. pneumoniae  and 10 months after the peak in respiratory virus detection . The peak GNB detection occurred 2 months after the peak mean monthly temperature . The peak in detection of S. pneumoniae occurred at the peak in detection of respiratory viruses .The peak in antibiotic prescriptions filled occurred 3 months before the peak in detection of C. difficile occurred a few months after the peak in antibiotic prescriptions during winter months, as previously described [C. difficile infections 1–2 months after peak macrolide and fluoroquinolone use [Peak detection of escribed , 8. Prevlone use .S. pneumoniae (0-month lag with OR = 1.01) as previously reported [We previously reported peaks of MRSA infections during the summer and autumn seasons . This sereported .Klebsiella spp.  and A. baumannii  [Our findings are similar to a study of 132 US hospitals that found higher outdoor temperatures associated with an increased frequency of bloodstream infections caused by GNB . A revie07–1.34) . However07–1.34) .There are limitations of this study. We collected de-identified data using infection control software rather than detailed medical record data. Misclassification bias may be present because we could not exclude clinically-insignificant microbial colonizers or bystanders which may have overestimated the number of true infections. We may have had selection bias since the microbiologic data was collected within our hospital system and outpatient facilities served by our microbiology laboratory and this data may not be reflective of all Rhode Islanders. Respiratory viral infections in children could have a different seasonal pattern compared to adults. There may be detection bias since healthcare providers may not have thought of ordering tests for respiratory virus detection outside of the winter season. In addition, there may have been a change in the denominator population captured over the time course that could potentially influence these findings. Since this is an ecological study, the temporal association can be easily confounded with other factors that are seasonal such as duration of antibiotics and the level of humidity. Viruses and bacteria in this study were detected in patients in one of our three acute care hospitals which comprises 55% of non-Veteran’s Administration medical center acute care beds in Rhode Island, and at various outpatient settings in Rhode Island. Antibiotic prescription data was derived from a database that included people throughout Rhode Island, some of whom were not cared for in our healthcare system. Thus, we cannot associate antibiotic prescriptions filled and microbiologic test results on an individual level. Despite these potential limitations, we are not aware of other studies that assessed the relationships among bacterial pathogens, respiratory viruses, antibiotic exposure, and meteorological parameters in the same geographic region.C. difficile highlights the potential impact of robust antibiotic stewardship on reducing C. difficile risk. Prevention of respiratory viral infections may reduce risk of S. pneumoniae infections as previously described. A better understanding of the seasonality of GNB and MRSA may help to focus future infection prevention efforts. As such, continued research is needed to better understand why these infections follow seasonal patterns.In conclusion, we attempted to study the complex ecology of bacterial and viral infections, and assess the potential impact of antibiotic exposure and climactic fluctuations. The temporal association between antibiotic prescriptions filled with detection of Additional file 1:Figure S1. Trend of positive respiratory viral panel (RVP) testing over time. (PNG 30 kb)


Antibiotic use in low-income and middle-income countries continues to rise despite the knowledge that antibiotic overuse can lead to antimicrobial resistance. There is a paucity of detailed data on the use of antibiotics in primary care in low-resource settings.To describe the presentation of acute infections and the indications for antibiotic prescription.A 2-year retrospective review of routinely collected data.All 32 primary care units in one district in northern Thailand.Patients attending primary care with a history of fever, documented temperature, International Statistical Classification of Diseases 10 code for infection or prescribed a systemic antibiotic. Patients attending after the initiation of a study on C-reactive protein testing in four centres were excluded.The proportion of patients prescribed an antibiotic and the frequency of clinical presentations.762 868 patients attended the health centres, of whom 103 196 met the inclusion criteria, 5966 were excluded resulting in 97 230 attendances consisting of 83 661 illness episodes.46.9% (39 242) of the patients were prescribed an antibiotic during their illness. Indications for antibiotic prescription in the multivariable logistic regression analysis included male sex (adjusted OR (aOR) 1.21 (95% CI 1.16 to 1.28), p<0.001), adults (aOR 1.77 (95% CI 1.57 to 2), p<0.001) and a temperature >37.5°C (aOR 1.24 (95% CI 1.03 to 1.48), p=0.020). 77.9% of the presentations were for respiratory-related problems, of which 98.6% were upper respiratory tract infections. The leading infection diagnoses were common cold (50%), acute pharyngitis (18.9%) and acute tonsillitis (5%) which were prescribed antibiotics in 10.5%, 88.7% and 87.1% of cases, respectively. Amoxicillin was the most commonly prescribed antibiotic.Nearly half of the patients received an antibiotic, the majority of whom had a respiratory infection. The results can be used to plan interventions to improve the rational use of antibiotics. Further studies in private facilities, pharmacies and dental clinics are required. Over 80 000 illness episodes reviewed from all primary care units in a district, over a 2-year time period.Wide range of infections included rather than focusing on one specific infection.Use of routine electronic data (no Hawthorne effect), making this work reproducible.Only included public healthcare facilities.Reliant on the correct coding and clinical diagnoses of illnesses.The proportion of global deaths attributable to communicable diseases has greatly reduced in recent years. Despite these improvements, 10.6% of deaths worldwide in 2015 were thought to be caused by lower respiratory tract infections (LRTIs), diarrhoea and tuberculosis (TB).7Overuse and misuse of antibiotics have been linked to the development of antimicrobial resistance (AMR).14To appreciate the scale of the problem and to target future interventions, a greater understanding of the acute infections presenting to primary care and the conditions for which antibiotics are used in LMICs is required. Such data, however, are limited,A retrospective computerised search of routinely collected data from PCUs in Mueang Chiang Rai District between January 2015 and December 2016 was carried out.Thailand is an upper-middle income country. In 2016, its gross domestic product was US$407 billion. The average life expectancy at birth is 75 years.Thailand’s healthcare system is made up of public and private providers. Universal health coverage was established in 2002 following significant investment in the healthcare system and infrastructure since the 1970s. In rural and poorer areas, primary healthcare is predominantly provided by the public healthcare system whereas in urban areas hospitals and private clinics play a larger role.19Antibiotics can be bought directly from pharmacies and local stores, as well as being prescribed by healthcare workers. Community antibiotic guidelines exist for some but not all common infections, including assessment criteria , first-line antibiotics, their dose and duration. There are prescribing restrictions in place for some broad-spectrum antibiotics such as amoxicillin and clavulanic acid (Co-amoxiclav) which cannot be prescribed by nurses working in the public primary care system. More comprehensive hospital-based guidelines are available.In Mueang Chiang Rai District, family medicine doctors based at the provincial hospital oversee 32 public PCUs which are staffed primarily by two to five nurses and public health officers. On average, PCUs look after 5000 patients each.Systemic antibiotic prescription.International Statistical Classification of Diseases (ICD) 10 code for infection .We excluded patients attending PCUs used as study sites during or after a recent trial on the use of C-reactive protein (CRP) point of care tests , a research data manager accessed the PHO’s routine medical records database to search for relevant patients and extract the prespecified variables. Data collected consisted of the PCU attended, patients’ number, age, sex, date of visit, chief complaint, temperature, ICD 10 code and drug prescriptions.The inclusion criteria were classified as being present, absent or that the data were missing. Antibiotics were searched for in the prescription field (free text) and coded as prescribed (yes or no). A predefined antibiotic list (see online Our predefined list of ICD 10 codes for infection (see online We searched for the word ‘fever’ in Thai in the chief complaint field (free text). In some cases ‘no fever’ was recorded, or the word ‘fever’ was present but part of a phrase alluding to a patient more generally, or ‘influenza vaccine’. This field was checked manually with the help of two native northern Thai speaking study nurses. History of fever in the chief complaint was then coded as yes or no. Documented temperatures over 37.5°C at the PCU were searched for in the temperature field and then coded as temperature >37.5°C yes or no.Repeat attendances within 1 month were classed as one illness episode allowing for the detection of subsequent antibiotics or treatment changes. All other indications such as the chief complaint and temperature were taken from the initial presentation. Children were defined as being under 12 years of age. The ICD 10 codes were grouped into gastrointestinal, respiratory, skin, urogenital, eye, ear and other categories. Each category was further broken down into conditions such as acute sinusitis and acute pharyngitis. The respiratory category was also grouped into URTI and LRTI.2 test.Categorical variables were summarised using counts and percentages. Non-normally distributed data were described using medians and IQRs and compared using the rank-sum test. The proportions of patients prescribed an antibiotic in different demographic groups were summarised and compared using the χA logistic regression model was used to model the binary outcome of antibiotic prescription (yes or no); both unadjusted and adjusted models were fitted and accounted for clustering of patients attending the same PCU. The ORs for the indications of antibiotic prescription were first obtained from univariate logistic regression models and then considered in a multivariable model if they had a p value of <0.05. In addition to these variables we also included documented temperature because this was considered to be a natural confounder of antibiotic prescription. Indications included sex, age category and documented temperature. The main purpose of this model was to identify risk factors that were independently associated with antibiotic prescription. A temperature of >37.5°C was used rather than the more subjective history of fever. ICD 10 codes were not included because of their strong association with antibiotic prescriptions . Furthermore, a Poisson regression model of the monthly number of antibiotic prescriptions over a 24-month period was produced to obtain the incidence rate ratios (IRRs) and 95% CIs.Monthly antibiotic prescriptions were weighted by the number of contributing PCUs per month and modelled over a 2-year period. When time-series analysis is used for forecasting, it is common to apply it to periods of 5 years or more; however, our aim was not to forecast into the future but to simply describe the current trends in antibiotic prescription.Similarly, a 12-month time-series window was used to obtain a trend line that would be sensitive to monthly changes but with reduced noise from seasonal variation:Where Patients were not involved in the design of the study. Due to the study’s retrospective nature, patients were not involved in the recruitment processes. Study results will be disseminated through community presentations and educational updates for the healthcare workers and community volunteers.A total of 762 868 patients attended the PCUs between 1 January 2015 and 31 December 2016. The majority of patients’ attendances included a chronic disease review or screening, the most common being screening for diseases such as diabetes, hypertension, mental health and dental disorders (145 410), essential hypertension reviews (98 822) and routine child health examinations (75 701).The appropriateness of the ICD 10 codes for infection used in our inclusion criteria were reviewed alongside the other variables. For example, we found that patients with TB, HIV and hepatitis B were only attending for regular medications rather than for acute illnesses so they were removed from the ICD 10 inclusion list. Mass head lice treatment at schools is carried out by the PCUs so these codes were also removed. The ICD 10 code ‘K05’  was also removed because it transpired that these patients were seen by dentists or dental nurses at the PCUs rather than by the regular PCU staff. All ICD 10 codes for myositis were removed from the inclusion criteria apart from M60.0 (infective myositis) because the other codes were being used for muscle pain or myalgia  meeting our inclusion and exclusion criteria. A total of 13 569 repeat attendances within 1 month were classed as a single illness episode, leaving 83 661 illness episodes.The median age was 24 years with an IQR of 6–51 years, two patients had no age recorded and 54.7% of the patients were female (45 779) compared with 45.3% males (37 882) (p<0.001).The proportion of patients meeting each inclusion criterion is shown in Medications were prescribed for 81 691 (97.7%) illness episodes; 37 011 (44.2%) patients were prescribed an antibiotic during their first visit, and this increased to 39 242 (46.9%) throughout their illness episodes.49.2% of males compared with 45% of females (p<0.001).39% of children compared with 51.8% of adults (p<0.001).40.1% of those with a history of fever.47.6% with a temperature >37.5°C.38.8% with an ICD 10 code for infection.Antibiotics were prescribed to:The proportion of patients within each age group prescribed an antibiotic varied, with the lowest rates in young children , peaking in adults  and then diminishing in the elderly  or dicloxacillin (25.1%). Other antibiotics prescribed include norfloxacin (8.9%), co-trimoxazole (4.2%), penicillin V (1.2%), roxithromycin (1.2%), metronidazole (1.2%), erythromycin (0.7%), cephalexin (0.4%) and tetracycline (0.2%).The number of acute presentations with ICD 10 codes for infection related to a single system are shown in Online 13.8% of patients (11 547) were prescribed antibiotics without a temperature, history of fever or ICD 10 code for infection, of those who had a single diagnosis recorded 1815 (24.6%) of these antibiotics were for dental reasons, 1002 (13.6%) for surgical follow-up care, 526 (7.1%) for contact dermatitis and 473 (6.4%) for open wounds  reduced from 54.5% to 25.4%.Our study also identifies high levels of prescribing for skin infections, otitis media, otitis externa, cystitis, hordeolum (styes) and chalazions. A lack of available topical antibiotics may account for the high prescribing for skin infections and otitis externa. However, despite antibacterial eyedrops being available, 15.7% of conjunctivitis cases were still prescribed a systemic antibiotic. Urine dipstick tests are not available on site to assess patients with cystitis or suspected urinary tract infections. Introduction of these simple tests may help to rationalise prescribing for these conditions in a setting where urine cultures are not readily available or achievable.While we did not set out to review dental prescribing, this area accounted for 25% of the antibiotics prescribed to those without a history of fever, temperature or ICD 10 code for infection which warrants further investigation.Some of the variation in antibiotic prescribing rates between PCUs may be accounted for by the degree of staff training. Two out of the three highest prescribing PCUs are staffed only by public health officers. The study findings are being used to guide educational updates and training for the PCU staff, with priority being given to those PCUs without nurses and with high prescription rates for conditions unlikely to require antibiotics.A wide range of antibiotics are prescribed in the PCUs. Restrictions are in place for some broad-spectrum antibiotics such as amoxicillin and clavulanic acid (Co-amoxiclav) which cannot be prescribed. One area of concern is that less than 1% of the antibiotics being prescribed have activity against scrub typhus which is the leading cause of hospital admission with acute undifferentiated fever in this region.35The main strength of this study is the large number of illness episodes included. The 2-year time period should allow for seasonal variations and disease epidemics. We reviewed prescribing in all of the PCUs in Mueang Chiang Rai District which covers a large geographical area and has a range of rural and urban facilities, making the results generalisable to the region more broadly. Many studies have focused on prescribing for specific conditions such as URTIs but our study covers a wide range of infections that present in the community. Having research staff on site has been shown to influence healthcare workers’ prescribing habits (the Hawthorne effect), but due to the retrospective nature of the study this was not a source of bias. The use of routinely collected data means that this methodology could be repeated in other districts and provinces in Thailand, although a lot of the data are entered as free text which presents challenges for analysis. Searching for patients with a history of fever, for instance, was problematic because the Thai word ‘ไข้’ or fever is also part of the Thai words for patient, influenza, antipyrexials and so on.Limitations of this study are that we only included public PCUs and have no data on antibiotic use by private clinics, pharmacies or family medicine doctors based at the provincial hospital which requires further study. The PCU data are taken from routine electronic records and in some instances there were tranches of missing data . Verifying the quality of some data is also challenging; coding of clinical diagnoses for instance using ICD 10 could be inconsistent between healthcare workers and in primary care the majority of infections are diagnosed clinically without any laboratory tests. However, we used data from a subsample of patients enrolled in a clinical trial in four PCUs and compared them with their respective routine medical records. While minor discrepancies were found in their precise age and temperature, the diagnoses and antibiotic prescribing data were consistent. Our decision to class all attendances within a 1-month period as a single illness episode means that we may have incorrectly classed some new illnesses as a repeat attendance but did allow us to review antibiotic prescribing over the course of the illness. The time series analysis was carried out using data from a 2-year time period, more definitive conclusions and trends may have become apparent if further time points and data were available.This study provides much needed insight into the use of antibiotics in primary care in northern Thailand, allowing targeting of interventions to improve the rational use of antibiotics. Nearly half of all patients attending with an acute illness received an antibiotic. The majority of presentations were for respiratory infections. Further education and resources are required to support clinicians in the targeting of antibiotics. This could include the introduction of clinical algorithms and point-of-care tests such as CRP and urine dipsticks. Antibiotic guidelines are required for common conditions seen in primary care outside of the current Antibiotic Smart Use policy. Further studies, including qualitative work, are required to appreciate the use of antibiotics in other settings such as private facilities, pharmacies and dental clinics.