Key lessons from the COVID-19 public health response in Australia.

Australia avoided the worst effects of the COVID-19 pandemic, but still experienced many negative impacts. Reflecting on lessons from Australia's public health response, an Australian expert panel composed of relevant discipline experts identified the following key lessons: 1) movement restrictions were effective, but their implementation requires careful consideration of adverse impacts, 2) disease modelling was valuable, but its limitations should be acknowledged, 3) the absence of timely national data requires re-assessment of national surveillance structures, 4) the utility of advanced pathogen genomics and novel vaccine technology was clearly demonstrated, 5) decision-making that is evidence informed and consultative is essential to maintain trust, 6) major system weaknesses in the residential aged-care sector require fixing, 7) adequate infection prevention and control frameworks are critically important, 8) the interests and needs of young people should not be compromised, 9) epidemics should be recognised as a 'standing threat', 10) regional and global solidarity is important. It should be acknowledged that we were unable to capture all relevant nuances and context specific differences. However, the intent of this review of Australia's public health response is to critically reflect on key lessons learnt and to encourage constructive national discussion in countries across the Western Pacific Region.

Hospitalisation for lower respiratory tract infection is associated with an increased incidence of acute myocardial infarction and stroke in tropical Northern Australia.

Acute respiratory infections appear to precipitate vascular events. Acute myocardial infarction (AMI) and stroke are the leading cause of death and disability globally. This study was based on a cohort of patients admitted to Townsville University Hospital between January 2006 and December 2016. Using a self-controlled case series design, we investigated the risk of AMI or ischaemic stroke after an episode of pneumonia. We defined the 'risk interval' as the first 14 days after hospitalisation for pneumonia and the 'control interval' as one year before and one year after the risk interval. Among a population (N = 4557) with a median age of over 70, a total of 128 AMI and 27 stroke cases were identified within 1 year of an episode of pneumonia in this study. Ten and two admissions occurred during the risk interval, while 118 and 25 admissions occurred during the control period. The relative incidence ratios (RIR) of AMI increased after an episode of pneumonia (RIR=4.85, 95% confidence interval (CI) 2.44-9.67). The risk for stroke after the exposure period of 14 days was 4.94 (95% CI 1.12-21.78) considering only the first stroke incidence. The RIR results for AMI and stroke were not altered by adjusting for age, sex or Indigenous status. The risk of AMI and stroke were significantly higher two weeks after an episode of pneumonia.

Is Nigeria really on top of COVID-19? Message from effective reproduction number.

Following the importation of coronavirus disease (COVID-19) into Nigeria on 27 February 2020 and then the outbreak, the question is: How do we anticipate the progression of the ongoing epidemic following all the intervention measures put in place? This kind of question is appropriate for public health responses and it will depend on the early estimates of the key epidemiological parameters of the virus in a defined population.In this study, we combined a likelihood-based method using a Bayesian framework and compartmental model of the epidemic of COVID-19 in Nigeria to estimate the effective reproduction number (R(t)) and basic reproduction number (R0) - this also enables us to estimate the initial daily transmission rate (ß0). We further estimate the reported fraction of symptomatic cases. The models are applied to the NCDC data on COVID-19 symptomatic and death cases from 27 February 2020 and 7 May 2020.In this period, the effective reproduction number is estimated with a minimum value of 0.18 and a maximum value of 2.29. Most importantly, the R(t) is strictly greater than one from 13 April till 7 May 2020. The R0 is estimated to be 2.42 with credible interval: (2.37-2.47). Comparing this with the R(t) shows that control measures are working but not effective enough to keep R(t) below 1. Also, the estimated fraction of reported symptomatic cases is between 10 and 50%.Our analysis has shown evidence that the existing control measures are not enough to end the epidemic and more stringent measures are needed.

Strategic investment in tuberculosis control in the Republic of Bulgaria.

As Bulgaria transitions away from Global Fund grant, robust estimates of the comparative impact of the various response strategies under consideration are needed to ensure sustained effectiveness of the tuberculosis (TB) programme. We tailored an established mathematical model for TB control to the epidemic in Bulgaria to project the likely outcomes of seven intervention scenarios. Under existing programmatic conditions projected forward, the country's targets for achieving TB elimination in the coming decades will not be achieved. No interventions under consideration were predicted to accelerate the baseline projected reduction in epidemiological indicators significantly. Discontinuation of the 'Open Doors' program and activities of non-governmental organisations would result in a marked exacerbation of the epidemic (increasing incidence in 2035 by 6-8% relative to baseline conditions projected forward). Changing to a short course regimen for multidrug-resistant TB (MDR-TB) would substantially decrease MDR-TB mortality (by 21.6% in 2035 relative to baseline conditions projected forward). Changing to ambulatory care for eligible patients would not affect TB burden but would be markedly cost-saving. In conclusion, Bulgaria faces important challenges in transitioning to a primarily domestically-financed TB programme. The country should consider maintaining currently effective programs and shifting towards ambulatory care to ensure program sustainability.

Is IPT more effective in high-burden settings? Modelling the effect of tuberculosis incidence on IPT impact.

SETTING: Isoniazid preventive therapy (IPT) is effective for preventing active tuberculosis (TB), although its mechanism of action is poorly understood and the optimal disease burden for IPT use has not been defined. OBJECTIVE: To describe the relationship between TB incidence and IPT effectiveness. METHODS: We constructed a model of TB transmission dynamics to investigate IPT effectiveness under various epidemiological settings. The model structure was intended to be highly adaptable to uncertainty in both input parameters and the mechanism of action of IPT. To determine the optimal setting for IPT use, we identified the lowest number needed to treat (NNT) with IPT to prevent one case of active TB. RESULTS: We found that the NNT as a function of TB incidence shows a 'U-shape', whereby IPT impact is greatest at an intermediate incidence and attenuated at both lower and higher incidence levels. This U-shape was observed over a broad range of parameter values; the optimal TB incidence was between 500 and 900 cases per 100 000 per year. CONCLUSIONS: TB burden is a critical factor to consider when making decisions about communitywide implementation of IPT. We believe that the total disease burden should not preclude programmatic application of IPT.

Heterogeneity of distribution of tuberculosis in Sheka Zone, Ethiopia: drivers and temporal trends.

OBJECTIVE: To describe the distribution of tuberculosis (TB) and its drivers in Sheka Zone, a geographically remote region of Ethiopia. METHODS: We collected data on TB patients treated from 2010 to 2014 in the Sheka Zone. Predictors of TB incidence were determined using a multivariate generalised linear regression model. RESULTS: We found significant spatial autocorrelation of TB incidence by kebele (the smallest administrative geographical subdivision in Ethiopia) (Moran's I = 0.3, P < 0.001). The average TB incidence per kebele ranged from 0 to 453 per 100 000 population per year, and was significantly associated with average TB incidence across adjacent kebeles, TB incidence in the same kebele in the previous year and health facility availability. Each increment in TB incidence by 10/100 000/year in adjacent kebeles or in a previous year was associated with an increase in TB incidence of respectively 3.0 and 5.5/100 000/year. Availability of a health centre was associated with an increase in TB incidence of 84.3/100 000. CONCLUSIONS: TB incidence in rural Ethiopia is highly heterogeneous, showing significant spatial autocorrelation. Both local transmission and access to health care are likely contributors to this pattern. Identification of local hotspots may assist in developing and optimising effective prevention and control strategies.

Long-term follow-up of contacts exposed to multidrug-resistant tuberculosis in Victoria, Australia, 1995-2010.

SETTING: The effectiveness of public health strategies following exposure to multidrug-resistant tuberculosis (MDR-TB) is not clear. OBJECTIVE: To perform long-term follow-up of MDR-TB contacts and review individual outcomes and management approaches. DESIGN: Retrospective review of MDR-TB contacts identified by the Victorian Department of Health from 1995 to 2010. Health records, including personal medical and pharmacy records and statewide clinical and laboratory TB databases, were searched to identify management strategies and individual outcomes. RESULTS: A total of 570 contacts of 47 MDR-TB cases were identified, with a total follow-up period of 3093 person-years of observation (PYO) since exposure. Of 570 contacts, 49 (8.6%) were considered likely to have been infected with Mycobacterium tuberculosis from index cases, and 11/49 (22.5%) of these were prescribed preventive therapy tailored to isolate susceptibility. No MDR-TB cases occurred in those receiving preventive treatment, while two cases were observed in those not treated (incidence 2878/100 000 PYO during the first 2 years post exposure). CONCLUSIONS: The risk of MDR-TB transmission to close contacts in this low-prevalence setting highlights the potential for public health strategies involving preventive treatment.

Estimating reproduction numbers for adults and children from case data.

We present a method for estimating reproduction numbers for adults and children from daily onset data, using pandemic influenza A(H1N1) data as a case study. We investigate the impact of different underlying transmission assumptions on our estimates, and identify that asymmetric reproduction matrices are often appropriate. Under-reporting of cases can bias estimates of the reproduction numbers if reporting rates are not equal across the two age groups. However, we demonstrate that the estimate of the higher reproduction number is robust to disproportionate data-thinning. Applying the method to 2009 pandemic influenza H1N1 data from Japan, we demonstrate that the reproduction number for children was considerably higher than that of adults, and that our estimates are insensitive to our choice of reproduction matrix.

Mannose-binding lectin and susceptibility to tuberculosis: a meta-analysis.

It has been proposed that mannose-binding lectin (MBL) levels may impact upon host susceptibility to tuberculosis (TB) infection; however, evidence to date has been conflicting. We performed a literature review and meta-analysis of 17 human trials considering the effect of MBL2 genotype and/or MBL levels and TB infection. No significant association was demonstrated between MBL2 genotype and pulmonary TB infection. However, the majority of studies did not report MBL2 haplotype inclusive of promoter polymorphisms. Serum MBL levels were shown to be consistently elevated in the setting of TB infection. While this may indicate that high MBL levels protect against infection with TB, the increase was also of a degree consistent with the acute-phase reaction. This analysis suggests that the relatively poorly characterized MBL2 genotypes reported are not associated significantly with susceptibility to pulmonary TB infection, but high MBL serum levels may be.

Estimating sensitivity and specificity from positive predictive value, negative predictive value and prevalence: application to surveillance systems for hospital-acquired infections.

Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) are terms usually associated with diagnostic testing. Although these concepts have been expanded from diagnostic assays to surveillance systems, these systems are not like diagnostic assays. In attempting to estimate the sensitivity and specificity of surveillance systems, situations may arise where only the PPV, NPV and prevalence are known. We aim to demonstrate the equivalence of two methods for calculating sensitivity and specificity from PPV, NPV and prevalence. The formulae for sensitivity and specificity are calculated from first principles and compared with the adjustment of a standard contingency table. We have illustrated this method using a review of a sample of surgical site infection cases following coronary artery bypass grafting. The derived prevalence from the sample is an estimate of the population prevalence and is the value that must be used in the formulae for sensitivity and specificity as functions of PPV, NPV and prevalence to obtain the same estimates as those obtained from the adjusted contingency table. The general proof of this principle is provided as an Appendix. The sensitivity and specificity of surveillance systems can be calculated by two equivalent methods when only PPV, NPV and prevalence are known.

Characterizing an outbreak of vancomycin-resistant enterococci using hidden Markov models.

BACKGROUND: Antibiotic-resistant nosocomial pathogens can arise in epidemic clusters or sporadically. Genotyping is commonly used to distinguish epidemic from sporadic vancomycin-resistant enterococci (VRE). We compare this to a statistical method to determine the transmission characteristics of VRE. METHODS AND FINDINGS: A structured continuous-time hidden Markov model (HMM) was developed. The hidden states were the number of VRE-colonized patients (both detected and undetected). The input for this study was weekly point-prevalence data; 157 weeks of VRE prevalence. We estimated two parameters: one to quantify the cross-transmission of VRE and the other to quantify the level of VRE colonization from sporadic sources. We compared the results to those obtained by concomitant genotyping and phenotyping. We estimated that 89% of transmissions were due to ward cross-transmission while 11% were sporadic. Genotyping found that 90% had identical glycopeptide resistance genes and 84% were identical or nearly identical on pulsed-field gel electrophoresis (PFGE). There was some evidence, based on model selection criteria, that the cross-transmission parameter changed throughout the study period. The model that allowed for a change in transmission just prior to the outbreak and again at the peak of the outbreak was superior to other models. This model estimated that cross-transmission increased at week 120 and declined after week 135, coinciding with environmental decontamination. SIGNIFICANCE: We found that HMMs can be applied to serial prevalence data to estimate the characteristics of acquisition of nosocomial pathogens and distinguish between epidemic and sporadic acquisition. This model was able to estimate transmission parameters despite imperfect detection of the organism. The results of this model were validated against PFGE and glycopeptide resistance genotype data and produced very similar results. Additionally, HMMs can provide information about unobserved events such as undetected colonization.

A stochastic mathematical model of methicillin resistant Staphylococcus aureus transmission in an intensive care unit: predicting the impact of interventions.

OBJECTIVES: To estimate the transmission rate of MRSA in an intensive care unit (ICU) in an 800 bed Australian teaching hospital and predict the impact of infection control interventions. METHODS: A mathematical model was developed which consisted of four compartments: colonised and uncolonised patients and contaminated and uncontaminated health-care workers (HCWs). Patient movements, MRSA acquisition and daily prevalence data were collected from an ICU over 939 days. Hand hygiene compliance and the probability of MRSA transmission from patient to HCW per discordant contact were measured during the study. Attack rate and reproduction ratio were estimated using Bayesian methods. The impact of a number of interventions on attack rate was estimated using both stochastic and deterministic versions of the model. RESULTS: The mean number of secondary cases arising from the ICU admission of colonised patients, also called the ward reproduction ratio, R(w), was estimated to be 0.50 (95% CI 0.39-0.62). The attack rate was one MRSA transmission per 160 (95% CI 130-210) uncolonised-patient days. Results were not sensitive to uncertainty in measured model parameters (hand hygiene rate and transmission probability per contact). Hand hygiene was predicted to be the most effective intervention. Decolonisation was predicted to be relatively ineffective. Increasing HCW numbers was predicted to increase MRSA transmission, in the absence of patient cohorting. The predictions of the stochastic model differed from those of the deterministic model, with lower levels of colonisation predicted by the stochastic model. CONCLUSIONS: The number of secondary cases of MRSA colonisation within the ICU in this study was below unity. Transmission of MRSA was sustained through admission of colonised patients. Stochastic model simulations give more realistic predictions in hospital ward settings than deterministic models. Increasing staff does not necessarily lead to reduced transmission of nosocomial pathogens.

Bayesian modelling of an epidemic of severe acute respiratory syndrome.

This paper analyses data arising from a SARS epidemic in Shanxi province of China involving a total of 354 people infected with SARS-CoV between late February and late May 2003. Using Bayesian inference, we have estimated critical epidemiological determinants. The estimated mean incubation period was 5.3 days (95% CI 4.2-6.8 days), mean time to hospitalisation was 3.5 days (95% CI 2.8-3.6 days), mean time from symptom onset to recovery was 26 days (95% CI 25-27 days) and mean time from symptom onset to death was 21 days (95% CI 16-26 days). The reproduction ratio was estimated to be 4.8 (95% CI 2.2-8.8) in the early part of the epidemic (February and March 2003) reducing to 0.75 (95% CI 0.65-0.85) in the later part of the epidemic (April and May 2003). The infectivity of symptomatic SARS cases in hospital and in the community was estimated. Community SARS cases caused transmission to others at an estimated rate of 0.4 per infective per day during the early part of the epidemic, reducing to 0.2 in the later part of the epidemic. For hospitalised patients, the daily infectivity was approximately 0.15 early in the epidemic, but fell to 0.0006 in the later part of the epidemic. Despite the lower daily infectivity level for hospitalised patients, the long duration of the hospitalisation led to a greater number of transmissions within hospitals compared with the community in the early part of the epidemic, as estimated by this study. This study investigated the individual infectivity profile during the symptomatic period, with an estimated peak infectivity on the ninth symptomatic day.

Comparison of contamination rates of catheter-drawn and peripheral blood cultures.

The aim of this study was to assess the sensitivity and specificity of catheter-drawn and peripheral blood cultures. Paired blood culture samples collected over a 44-month period from a 280 bed Brisbane metropolitan hospital were analysed, using standard clinical and microbiological criteria, to determine whether blood culture isolates represented true bacteraemias or contamination. Catheter-collected cultures had a specificity of 85% compared with 97% for peripheral cultures. In only two instances (0.2%) was the diagnosis of clinically significant bacteraemia made on the basis of catheter culture alone. This study concluded that catheter-collected samples are not a good test for true bacteraemia, and that peripheral cultures are more reliable when the results of the paired cultures are discordant.

An investigation of contact transmission of methicillin-resistant Staphylococcus aureus.

Hand hygiene is critical in the healthcare setting and it is believed that methicillin-resistant Staphylococcus aureus (MRSA), for example, is transmitted from patient to patient largely via the hands of health professionals. A study has been carried out at a large teaching hospital to estimate how often the gloves of a healthcare worker are contaminated with MRSA after contact with a colonized patient. The effectiveness of handwashing procedures to decontaminate the health professionals' hands was also investigated, together with how well different healthcare professional groups complied with handwashing procedures. The study showed that about 17% (9-25%) of contacts between a healthcare worker and a MRSA-colonized patient results in transmission of MRSA from a patient to the gloves of a healthcare worker. Different health professional groups have different rates of compliance with infection control procedures. Non-contact staff (cleaners, food services) had the shortest handwashing times. In this study, glove use compliance rates were 75% or above in all healthcare worker groups except doctors whose compliance was only 27%.