Predicting COVID-19 Cases in South Korea Using Stringency and Niño Sea Surface Temperature Indices.

Most coronavirus disease 2019 (COVID-19) models use a combination of agent-based and equation-based models with only a few incorporating environmental factors in their prediction models. Many studies have shown that human and environmental factors play huge roles in disease transmission and spread, but few have combined the use of both factors, especially for SARS-CoV-2. In this study, both man-made policies (Stringency Index) and environment variables (Niño SST Index) were combined to predict the number of COVID-19 cases in South Korea. The performance indicators showed satisfactory results in modeling COVID-19 cases using the Non-linear Autoregressive Exogenous Model (NARX) as the modeling method, and Stringency Index (SI) and Niño Sea Surface Temperature (SST) as model variables. In this study, we showed that the accuracy of SARS-CoV-2 transmission forecasts may be further improved by incorporating both the Niño SST and SI variables and combining these variables with NARX may outperform other models. Future forecasting work by modelers should consider including climate or environmental variables (i.e., Niño SST) to enhance the prediction of transmission and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Understanding chaos in COVID-19 and its relationship to stringency index: Applications to large-scale and granular level prediction models.

Understanding the underlying and unpredictable dynamics of the COVID-19 pandemic is important. We supplemented the findings of Jones and Strigul (2020) and described the chaotic behavior of COVID-19 using state space plots which depicted the changes in asymptotic behavior and trajectory brought about by the increase or decrease in the number of cases which resulted from the easing or tightening of restrictions and other non-pharmaceutical interventions instituted by governments as represented by the country's stringency index (SI). We used COVID-19 country-wide case count data and analyzed it using convergent cross-mapping (CCM) and found that the SI influence on COVID-19 case counts is high in almost all the countries considered. When we utilized finer granular geographical data ('barangay' or village level COVID-19 case counts in the Philippines), the effects of SI were reduced as the population density increased. The authors believe that the knowledge of the chaotic behavior of COVID-19 and the effects of population density as applied to finer granular geographical data has the potential to generate more accurate COVID-19 non-linear prediction models. This could be used at the local government level to guide strategic and highly targeted COVID-19 policies which are favorable to public health systems but with limited impact to the economy.

First report of the mcr-1 colistin resistance gene identified in two Escherichia coli isolates from clinical samples, Philippines, 2018.

OBJECTIVES: The first report of a plasmid-borne colistin resistance gene (mcr-1) detected in an Escherichia coli isolate from China heralded the emergence of pandrug-resistant bacteria. Since then, the mcr-1 gene has been detected worldwide, but to date it has not been reported in the Philippines. METHODS: In this study, 123 antimicrobial-resistant isolates collected from January-June 2018 from patients admitted to a tertiary hospital in Manila, Philippines, were characterised. Biochemical identification and antimicrobial susceptibility testing were performed using a BD Phoenix™ M50 system with NMIC/ID-95 panel. Conventional PCR was performed to detect the genes mcr-1 to mcr-5, and short- and long-read whole-genome sequencing was performed. RESULTS: Two mcr-1-positive E. coli clinical isolates from separate patients harboured mcr-1 on an IncI2 plasmid. One isolate was shown to carry 12 antimicrobial resistance genes (ARGs) in addition to mcr-1, including the extended-spectrum ß-lactamase blaCTX-M-55, whilst the other E. coli isolate carried 6 ARGs in addition to mcr-1. CONCLUSION: Both patients had no prior colistin treatment recorded in their medical history and no travel history outside of the country within the past 6 months from the date of hospital admission, indicating local transmission and acquisition of the colistin-resistant strain from either community or hospital settings within the Philippines. This report should serve as a signal to local public-health officials of the need to intensify surveillance efforts and to increase vigilance and implementation of antimicrobial stewardship programmes to contain and slow the spread of antimicrobial resistance.

Retrospective use of next-generation sequencing reveals the presence of Enteroviruses in acute influenza-like illness respiratory samples collected in South/South-East Asia during 2010-2013.

BACKGROUND: Emerging and re-emerging respiratory pathogens represent an increasing threat to public health. Etiological determination during outbreaks generally relies on clinical information, occasionally accompanied by traditional laboratory molecular or serological testing. Often, this limited testing leads to inconclusive findings. The Armed Forces Research Institute of Medical Sciences (AFRIMS) collected 12,865 nasopharyngeal specimens from acute influenza-like illness (ILI) patients in five countries in South/South East Asia during 2010-2013. Three hundred and twenty-four samples which were found to be negative for influenza virus after screening with real-time RT-PCR and cell-based culture techniques demonstrated the potential for viral infection with evident cytopathic effect (CPE) in several cell lines. OBJECTIVE: To assess whether whole genome next-generation sequencing (WG-NGS) together with conventional molecular assays can be used to reveal the etiology of influenza negative, but CPE positive specimens. STUDY DESIGN: The supernatant of these CPE positive cell cultures were grouped in 32 pools containing 2-26 supernatants per pool. Three WG-NGS runs were performed on these supernatant pools. Sequence reads were used to identify positive pools containing viral pathogens. Individual samples in the positive pools were confirmed by qRT-PCR, RT-PCR, PCR and Sanger sequencing from the CPE culture and original clinical specimens. RESULTS: WG-NGS was an effective way to expand pathogen identification in surveillance studies. This enabled the identification of a viral agent in 71.3% (231/324) of unidentified surveillance samples, including common respiratory pathogens (100/324; 30.9%): enterovirus (16/100; 16.0%), coxsackievirus (31/100; 31.0%), echovirus (22/100; 22.0%), human rhinovirus (3/100; 3%), enterovirus genus (2/100; 2.0%), influenza A (9/100; 9.0%), influenza B, (5/100; 5.0%), human parainfluenza (4/100; 4.0%), human adenovirus (3/100; 3.0%), human coronavirus (1/100; 1.0%), human metapneumovirus (2/100; 2.0%), and mumps virus (2/100; 2.0%), in addition to the non-respiratory pathogen herpes simplex virus type 1 (HSV-1) (172/324; 53.1%) and HSV-1 co-infection with respiratory viruses (41/324; 12.7%).

Region-wide synchrony and traveling waves of dengue across eight countries in Southeast Asia.

Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼ 10(7) km(2). We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.

Demographic, clinical and laboratory findings among adult and pediatric patients hospitalized with dengue in the Philippines.

We evaluated the differences in demographic, clinical, and laboratory findings between adult and pediatric patients hospitalized with dengue fever. Ninety patients with dengue infection admitted at San Lazaro Hospital (SLH), Manila from September 2005 to January 2006 were included in the study. The cases were laboratory-confirmed to have dengue infection. The majority of dengue cases (92%) had secondary dengue infection (median age = 18, age range: 2-37) while the remainder (8%) had a primary dengue infection (median age = 12, age range: 7-22). Nearly all the patients (99%) had dengue hemorrhagic fever (DHF). Sixty-five of the cases (72%) had serotype data: 2 (3%) were dengue virus serotype 1 (DENV-1) (median age = 17), 12 (18%) had DENV-2 (median age = 17.5), 38 (59%) had DENV-3 (median age = 16) and 13 (20%) had DENV-4 (median age = 18). The initial signs, symptoms and laboratory results except hematocrit (p = 0.02) and hemoglobin (p = 0.02) did not differ significantly between adults and children. During the study period, half the cases were adults (218 years; n = 45) and half were children (<18 years; n = 45). The ages of cases ranged from 2 to 37 years (median = 17 years) and the peak incidence was 15-19 years. Dengue is often considered as a pediatric disease. Additional studies are needed to determine if an age shift is occurring and where.

Prediction of high incidence of dengue in the Philippines.

BACKGROUND: Accurate prediction of dengue incidence levels weeks in advance of an outbreak may reduce the morbidity and mortality associated with this neglected disease. Therefore, models were developed to predict high and low dengue incidence in order to provide timely forewarnings in the Philippines. METHODS: Model inputs were chosen based on studies indicating variables that may impact dengue incidence. The method first uses Fuzzy Association Rule Mining techniques to extract association rules from these historical epidemiological, environmental, and socio-economic data, as well as climate data indicating future weather patterns. Selection criteria were used to choose a subset of these rules for a classifier, thereby generating a Prediction Model. The models predicted high or low incidence of dengue in a Philippines province four weeks in advance. The threshold between high and low was determined relative to historical incidence data. PRINCIPAL FINDINGS: Model accuracy is described by Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, and Specificity computed on test data not previously used to develop the model. Selecting a model using the F0.5 measure, which gives PPV more importance than Sensitivity, gave these results: PPV = 0.780, NPV = 0.938, Sensitivity = 0.547, Specificity = 0.978. Using the F3 measure, which gives Sensitivity more importance than PPV, the selected model had PPV = 0.778, NPV = 0.948, Sensitivity = 0.627, Specificity = 0.974. The decision as to which model has greater utility depends on how the predictions will be used in a particular situation. CONCLUSIONS: This method builds prediction models for future dengue incidence in the Philippines and is capable of being modified for use in different situations; for diseases other than dengue; and for regions beyond the Philippines. The Philippines dengue prediction models predicted high or low incidence of dengue four weeks in advance of an outbreak with high accuracy, as measured by PPV, NPV, Sensitivity, and Specificity.

Hospital-based surveillance of Japanese encephalitis at a tertiary hospital in Manila.

Japanese encephalitis virus (JEV) is endemic in the Philippines but the incidence and burden of disease are not well established. We conducted a prospective hospital-based study at San Lazaro Hospital, a tertiary level hospital in Manila, from September 2005 to December 2006. Cases were determined using an in-house dengue and Japanese encephalitis (JE) enzyme-linked immunosorbent assay in order to detect the proportion of JE cases among the acute encephalitis syndrome (AES) cases admitted to our hospital. Fifteen patients were found to have AES, of whom 6 (40%) had confirmed JE. Of the JE cases, 4 were females and 2 were males with an age range of 3-14 years. Three of the 6 JE cases occurred during July. The most common signs and symptoms on admission among JE cases were: fever, headache, loss of appetite, neck rigidity and altered sensorium. JE likely comprises a significant proportion of hospitalized AES cases among children from Manila and nearby provinces. Further studies on the nation-wide prevalence and distribution of JE in the Philippines are needed to guide health authorities in disease control and prevention strategies.

Applications of PCR (real-time and MassTag) and enzyme-linked immunosorbent assay in diagnosis of respiratory infections and diarrheal illness among deployed U.S. military personnel during exercise Balikatan 2009, Philippines.

Laboratory-based surveillance for diarrheal and respiratory illness was conducted at the 2009 Republic of the Philippines-United States Balikatan exercise to determine the presence of specific pathogens endemic in the locations where the military exercises were conducted. Ten stool and 6 respiratory specimens were obtained from individuals meeting case definitions for diarrhea or respiratory illness. Stool specimens were frozen in dry ice and remotely tested using enzyme-linked immunosorbent assay for Rotavirus, Astrovirus, Adenovirus, Entamoeba histolytica, Giardia, and Cryptosporidium and polymerase chain reaction for enterotoxigenic Escherichia coli, Campylobacter, Shigella, Vibrio, Salmonella, and Norovirus. Eight (4 for Campylobacter jejuni, 2 for Campylobacter coli, 1 for Norovirus genogroup II, and 1 for both Campylobacter coli and enterotoxigenic Escherichia coli) of 10 samples were positive for at least 1 enteric pathogen. MassTag polymerase chain reaction for influenza A and B, respiratory syncytial virus groups A and B, human coronavirus-229E and human coronavirus-OC43, human metapneumovirus, enterovirus, human parainfluenza viruses 2,3, and 4a, human adenovirus, Haemophilus influenzae, Neisseria meningitidis, Streptococcus pneumoniae, Legionella pneumonia, and Mycoplasma pneumonia was done on respiratory specimens. Out of 6 samples, 3 tested positive for H. influenzae; 1 tested positive for both H. influenzae and human parainfluenza virus 3; and 2 tested negative. Laboratory-based surveillance can be useful in determining etiologies of diarrheal and respiratory illness of deployed military personnel.

Department of Defense influenza and other respiratory disease surveillance during the 2009 pandemic.

The Armed Forces Health Surveillance Center's Division of Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) supports and oversees surveillance for emerging infectious diseases, including respiratory diseases, of importance to the U.S. Department of Defense (DoD). AFHSC-GEIS accomplishes this mission by providing funding and oversight to a global network of partners for respiratory disease surveillance. This report details the system's surveillance activities during 2009, with a focus on efforts in responding to the novel H1N1 Influenza A (A/H1N1) pandemic and contributions to global public health. Active surveillance networks established by AFHSC-GEIS partners resulted in the initial detection of novel A/H1N1 influenza in the U.S. and several other countries, and viruses isolated from these activities were used as seed strains for the 2009 pandemic influenza vaccine. Partners also provided diagnostic laboratory training and capacity building to host nations to assist with the novel A/H1N1 pandemic global response, adapted a Food and Drug Administration-approved assay for use on a ruggedized polymerase chain reaction platform for diagnosing novel A/H1N1 in remote settings, and provided estimates of seasonal vaccine effectiveness against novel A/H1N1 illness. Regular reporting of the system's worldwide surveillance findings to the global public health community enabled leaders to make informed decisions on disease mitigation measures and controls for the 2009 A/H1N1 influenza pandemic. AFHSC-GEIS's support of a global network contributes to DoD's force health protection, while supporting global public health.

Evaluation of QuickVue influenza A+B rapid test for detection of pandemic influenza A/H1N1 2009.

BACKGROUND: A novel influenza A/H1N1 emerged in early 2009 and by June 2009 was declared a pandemic by WHO. Rapid influenza antigen detection tests have been used to diagnose seasonal influenza but have not been adequately evaluated for the pandemic strain among all age groups. In the Philippines, pandemic influenza A/H1N1 2009 was first detected in May 2009 and by July 2009, 3207 cases and 6 deaths were reported. OBJECTIVES: Using RT-PCR as the gold standard, clinical sensitivity/specificity of Quidel QuickVue (QV) influenza A+B was estimated across all age groups for pandemic influenza A/H1N1 using nasal swabs in a hospital setting. Effect of age, viral titers (Ct values), and timing of collection on QV sensitivity to detect pandemic influenza A/H1N1 2009 was also determined. STUDY DESIGN: Febrile patients with influenza-like illness (n=360) at the V. Luna General Hospital, Manila from 1 June to 31 August 2009 were included. Nasal swabs were tested using QV and RT-PCR. RESULTS: Of 360 nasal specimens 226 (63%) were positive for pandemic influenza A/H1N1. QV sensitivity was 63% (95% confidence interval (CI): 56-69%), specificity was 96% (95% CI: 91-99%), positive predictive value was 97% (CI: 93-99%), and negative predictive value was 57% (95% CI: 49-64%). Patient's age, fever severity, presenting symptoms or number of symptoms did not significantly affect QV sensitivity, however QV sensitivity was correlated with decreasing Ct values. CONCLUSION: QuickVue demonstrated moderate sensitivity for pandemic influenza A/H1N1 infection. There was a significant inverse association between Ct values and QV sensitivity for pandemic influenza A/H1N1.