Healthcare workers' acceptance of the integrated tuberculosis-COVID-19 screening in central Java Private Hospitals, Indonesia.

Objective: COVID-19 pandemic has negatively impacted the diagnosis and management of tuberculosis (TB) cases, and TB-COVID-19 integrated screening was introduced as a strategy to overcome these problems. This study determined the acceptability of the TB-COVID-19 integrated screening by healthcare workers (HCWs) and its impact on achievement of the TB program. Methods: This was a mixed-method study with an embedded design. Data on hospital TB program coverage from the national TB information system for all Muhammadiyah and Aisyiyah Hospitals (MAHs) in Central Java were compared before and after the implementation of TB-COVID-19 integrated screening. The informants consisted of HCWs from 21 MAHs in Central Java. Focus group discussions (FGDs) were carried out with 7 hospital TB, 19 emergency room, 10 outpatient, 6 inpatient, and 4 managerial staff. In-depth interview (IDIs) were also performed with the Technical Officer TB Recovery Head of the Muhammadiyah Center. All IDIs and FGDs were recorded, transcribed verbatim, and subjected to thematic analysis guided by the theoretical framework of acceptability (TFA). Result: Implementation of the TB-COVID-19 integrated screening program led to an increase in the number of new TB case diagnoses at the Central Java Hospitals. Moreover, the program was acceptable based on seven indicators from TFA. Despite the obstacles faced by HCWs during the implementation process, the program still managed to meet the standards. Conclusion: Acceptance by HCWs is a critical factor in the successful implementation of programs, including the TB-COVID-19 integrated screening. Furthermore, a multifaceted and cross-sectoral approach is required to address the constraints associated with the process.

Bidirectional screening and testing for TB and COVID-19 among outpatient department attendees: outcome of an initial intervention in Ghana.

BACKGROUND: Tuberculosis (TB) remains a major public health threat in Ghana. The impact of COVID-19 resulted in a 15% decline of TB case notification in 2020 compared to 2019. To mitigate the impact on TB services, the Ghana National Tuberculosis Programme (NTP) introduced the bidirectional screening and testing for TB and COVID-19 in 2021. OBJECTIVE: To evaluate the yield of bidirectional screening and testing for TB and COVID-19 among facility attendees in the Greater Accra region. METHOD: We used secondary data obtained from the initial implementation stage of the bidirectional testing for TB and COVID-19 among COVID-19 and/or TB presumed cases in five health facilities in the Greater Accra Region from January to March 2021. To mitigate the impact of COVID-19 on TB services and accelerate TB case detection, the NTP of Ghana introduced bidirectional screening and testing for TB and COVID-19 in Greater Accra Region before scaling up at national level. RESULTS: A total of 208 presumed TB or COVID-19 cases were identified: 113 were tested for COVID-19 only, and 94 were tested for both TB and COVID-19, 1 was tested for TB only. Among presumed cases tested for COVID-19, 9.7% (95% CI, 5.6-13.7%) were tested positive. Whilst among the total presumed tested for TB, 13.7% (95% CI, 6.8-20.6%) were confirmed to have TB. Among the total 94 presumed cases tested for both TB and COVID-19, 11.7% (95% CI, 5.2-18.2%) were confirmed to have TB and 13.8% (95% CI, 6.9-20.8%) participants were COVID-19 positive and one participant (1.1%) had both COVID-19 and TB. CONCLUSION: Bidirectional screening and testing for TB and COVID-19 shows significant potential for improving overall case detection for the two diseases. The bidirectional screening and testing could be applicable to address a similar respiratory epidemic in the future that might have a masking effect on the response to TB disease.

Implementation of evidence-based multiple focus integrated intensified TB screening to end TB (EXIT-TB) package in East Africa: a qualitative study.

INTRODUCTION: Tuberculosis (TB) remains a major cause of morbidity and mortality, especially in sub-Saharan Africa. We qualitatively evaluated the implementation of an Evidence-Based Multiple Focus Integrated Intensified TB Screening package (EXIT-TB) in the East African region, aimed at increasing TB case detection and number of patients receiving care. OBJECTIVE: We present the accounts of participants from Tanzania, Kenya, Uganda, and Ethiopia regarding the implementation of EXIT-TB, and suggestions for scaling up. METHODS: A qualitative descriptive design was used to gather insights from purposefully selected healthcare workers, community health workers, and other stakeholders. A total of 27, 13, 14, and 19 in-depth interviews were conducted in Tanzania, Kenya, Uganda, and Ethiopia respectively. Data were transcribed and translated simultaneously and then thematically analysed. RESULTS: The EXIT-TB project was described to contribute to increased TB case detection, improved detection of Multidrug-resistant TB patients, reduced delays and waiting time for diagnosis, raised the index of TB suspicion, and improved decision-making among HCWs. The attributes of TB case detection were: (i) free X-ray screening services; (ii) integrating TB case-finding activities in other clinics such as Reproductive and Child Health clinics (RCH), and diabetic clinics; (iii), engagement of CHWs, policymakers, and ministry level program managers; (iv) enhanced community awareness and linkage of clients; (v) cooperation between HCWs and CHWs, (vi) improved screening infrastructure, (vii) the adoption of the new simplified screening criteria and (viii) training of implementers. The supply-side challenges encountered ranged from disorganized care, limited space, the COVID-19 pandemic, inadequate human resources, inadequate knowledge and expertise, stock out of supplies, delayed maintenance of equipment, to absence of X-ray and GeneXpert machines in some facilities. The demand side challenges ranged from delayed care seeking, inadequate awareness, negative beliefs, fears towards screening, to financial challenges. Suggestions for scaling up ranged from improving service delivery, access to diagnostic equipment and supplies, and infrastructure, to addressing client fears and stigma. CONCLUSION: The EXIT-TB package appears to have contributed towards increasing TB case detection and reducing delays in TB treatment in the study settings. Addressing the challenges identified is needed to maximize the impact of the EXIT-TB intervention.

Long COVID active case detection initiative among COVID-19 patients in Port Dickson, Malaysia: a retrospective study on the positive outcomes, the proportion of patients with long COVID and its associated factors.

Background: Long COVID is new or ongoing symptoms at four weeks or more after the start of acute COVID-19. However, the prevalence and factors associated with long COVID are largely unknown in Malaysia. We aim to determine the proportion and factors associated with long COVID among COVID-19 patients in Port Dickson, Malaysia. The positive outcomes of our long COVID active detection initiative were also described. Methods: This was a retrospective analysis of long COVID data collected by the Port Dickson District Health Office between 1 September 2021 to 31 October 2021. Monitoring long COVID symptoms was our quality improvement initiative to safeguard residents' health in the district. The study population was patients previously diagnosed with COVID-19 who resided in Port Dickson. The inclusion criteria were adults aged 18 years and above and were in the fifth week (day 29 to 35) post-COVID-19 diagnosis during the data collection period. We called all consecutive eligible patients to inquire regarding long COVID symptoms. Long COVID was defined as new or ongoing symptoms lasting more than 28 days from the date of positive SARS-CoV-2 by polymerase chain reaction test. Binary multivariate logistic regression was conducted to determine factors associated with long COVID. Results: Among 452 patients, they were predominantly male (54.2%), Malays (68.8%) and aged 18-29 years (58.6%). A total of 27.4% (95% CI [23.4-31.8]) of patients experienced long COVID symptoms and were referred to government clinics. The most frequent long COVID symptoms experienced were fatigue (54.0%), cough (20.2%), muscle pain (18.5%), headache (17.7%) and sleep disturbance (16.1%). Females, patients with underlying cardiovascular disease, asthma and chronic obstructive airway disease, those who received symptomatic care, and patients with myalgia and headaches at COVID-19 diagnosis were more likely to have long COVID. Three patients with suspected severe mental health problems were referred to the district psychologist, and ten patients with no/incomplete vaccination were referred for vaccination. Conclusion: Long COVID is highly prevalent among COVID-19 patients in Port Dickson, Malaysia. Long-term surveillance and management of long COVID, especially among the high-risk groups, are needed as we transition to living with COVID-19.

Third wave of COVID-19: mathematical model with optimal control strategy for reducing the disease burden in Nigeria.

The study of COVID-19 pandemic which paralyzed global economy of countries is a crucial research area for effective future planning against other epidemics. Unfortunately, we now have variants of the disease resulting to what is now known as waves of the pandemic. Several mathematical models have been developed to study this disease. While recent models incorporated control measures, others are without optimal control measures or demographic parameters. In this study, we propose a deterministic compartmental epidemiological model to study the transmission dynamic of the spread of the third wave of the pandemic in Nigeria, and we incorporated optimal control measures as strategies to reduce the burden of the deadly disease. Specifically, we investigated the transmission dynamics of COVID-19 model without demographic features. We then conducted theoretical analysis of the model with and without optimal control strategy. In the model without optimal control, we computed the reproduction number, an epidemiological threshold useful for bringing the third wave of the pandemic under check in Nigeria, and we proofed the disease stability and conducted sensitivity analysis in order to identify parameters that can impact the reproduction number tremendously. In a similar reasoning, for the model with control strategy, we check the necessary condition for the model. To validate our theoretical analyses, we illustrated the applications of the proposed model using COVID-19 data for Nigeria for a period when the country was under the yoke of the third wave of the disease. The data were then fitted to the model, and we derived a predictive tool toward making a forecast for the cumulative number of cases of infection, cumulative number of active cases and the peak of the third wave of the pandemic. From the simulations, it was observed that the presence of optimal control parameters leads to significant impact on the reduction of the spread of the disease. However, it was discovered that the success of the control of the disease relies on the proper and effective implementation of the optimal control strategies efficiently and adequately.

Malaysian Enhanced Movement Control Order (EMCO): a unique and impactful approach to combating pandemic COVID-19

Purpose - The paper highlights the process-handling during the Enhanced Movement Control Order (EMCO) in combating pandemic COVID-19 in Malaysia. Design/methodology/approach - Malaysia first issued an EMCO following a cluster that involved a religious gathering. The EMCO was issued to lockdown the area, undertake screening, treat positive cases and quarantine their close contacts. Active case detection and mass sampling were the main activities involving the population in both zones. Findings - One hundred ninety-three confirmed COVID-19 cases were identified from the total population of 2,599. Of these cases, 99.5% were Malaysians, 31.7% were aged >60 years and all four deaths (Case Fatality Rate, 2.1%) were elderly people with comorbidities. One hundred and one cases (52.3%) were asymptomatic, of which 77 (77%) were detected during mass sampling. The risk factors contributing to the outbreak were contacts that had attended the religious gathering, regular mosque congregants, wedding ceremony attendees and close household contacts. Malaysia implemented an effective measure in the form of the EMCO to contain the COVID-19 outbreak, where the last cases were reported 16 days before the EMCO was lifted. Originality/value - The residents' compliance and inter-agency cooperation were essential elements to the success of the EMCO. A targeted approach using an EMCO should be implemented in a future pandemic.

Statistical modelling of COVID-19 data: Putting generalized additive models to work

Over the course of the COVID-19 pandemic, Generalized Additive Models (GAMs) have been successfully employed on numerous occasions to obtain vital data-driven insights. In this article we further substantiate the success story of GAMs, demonstrating their flexibility by focusing on three relevant pandemic-related issues. First, we examine the interdepency among infections in different age groups, concentrating on school children. In this context, we derive the setting under which parameter estimates are independent of the (unknown) case-detection ratio, which plays an important role in COVID-19 surveillance data. Second, we model the incidence of hospitalizations, for which data is only available with a temporal delay. We illustrate how correcting for this reporting delay through a nowcasting procedure can be naturally incorporated into the GAM framework as an offset term. Third, we propose a multinomial model for the weekly occupancy of intensive care units (ICU), where we distinguish between the number of COVID-19 patients, other patients and vacant beds. With these three examples, we aim to showcase the practical and ‘off-the-shelf’ applicability of GAMs to gain new insights from real-world data. [ FROM AUTHOR] Copyright of Statistical Modelling: An International Journal is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Geospatial analytics for COVID-19 active case detection

Ever since the COVID-19 pandemic started in Wuhan, China, much research work has been focusing on the clinical aspect of SARS-CoV-2. Researchers have been leveraging on various Artificial Intelligence techniques as an alternative to medical approach in understanding the virus. Limited studies have, however, reported on COVID-19 transmission pattern analysis, and using geography features for prediction of potential outbreak sites. Predicting the next most probable outbreak site is crucial, particularly for optimizing the planning of medical personnel and supply resources. To tackle the challenge, this work proposed distance-based similarity measures to predict the next most probable outbreak site together with its magnitude, when would the outbreak likely to happen and the duration of the outbreak. The work began with preprocessing of 1365 patient records from six districts in the most populated state named Selangor in Malaysia. The dataset was then aggregated with population density information and human elicited geography features that might promote the transmission of COVID-19. Empirical findings indicated that the proposed unified decision-making approach outperformed individual distance metric in predicting the total cases, next outbreak location, and the time interval between start dates of two similar sites. Such findings provided valuable insights for policymakers to perform Active Case Detection. © 2021 Tech Science Press. All rights reserved.

Mathematical analysis of the dynamics of COVID-19 in Africa under the influence of asymptomatic cases and re-infection.

Coronavirus pandemic (COVID-19) hit the world in December 2019, and only less than 5% of the 15 million cases were recorded in Africa. A major call for concern was the significant rise from 2% in May 2020 to 4.67% by the end of July 15, 2020. This drastic increase calls for quick intervention in the transmission and control strategy of COVID-19 in Africa. A mathematical model to theoretically investigate the consequence of ignoring asymptomatic cases on COVID-19 spread in Africa is proposed in this study. A qualitative analysis of the model is carried out with and without re-infection, and the reproduction number is obtained under re-infection. The results indicate that increasing case detection to detect asymptomatically infected individuals will be very effective in containing and reducing the burden of COVID-19 in Africa. In addition, the fact that it has not been confirmed whether a recovered individual can be re-infected or not, then enforcing a living condition where recovered individuals are not allowed to mix with the susceptible or exposed individuals will help in containing the spread of COVID-19.

Probability-Based Estimates of Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence and Detection Fraction, Utah, USA.

We aimed to generate an unbiased estimate of the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 4 urban counties in Utah, USA. We used a multistage sampling design to randomly select community-representative participants >12 years of age. During May 4-June 30, 2020, we collected serum samples and survey responses from 8,108 persons belonging to 5,125 households. We used a qualitative chemiluminescent microparticle immunoassay to detect SARS-CoV-2 IgG in serum samples. We estimated the overall seroprevalence to be 0.8%. The estimated seroprevalence-to-case count ratio was 2.5, corresponding to a detection fraction of 40%. Only 0.2% of participants from whom we collected nasopharyngeal swab samples had SARS-CoV-2-positive reverse transcription PCR results. SARS-CoV-2 antibody prevalence during the study was low, and prevalence of PCR-positive cases was even lower. The comparatively high SARS-CoV-2 detection rate (40%) demonstrates the effectiveness of Utah's testing strategy and public health response.

Policy disparities in response to COVID-19 between Singapore and China.

OBJECTIVE: The study analyzed the common points and discrepancies of COVID-19 control measures of the two countries in order to provide appropriate coping experiences for countries all over the world. METHOD: This study examined the associations between the epidemic prevention and control policies adopted in the first 70 days after the outbreak and the number of confirmed cases in China and Singapore using the generalized linear model. Policy comparisons and disparities between the two countries were also discussed. RESULTS: The regression models show that factors influencing the cumulative number of confirmed cases in China: Locking down epicenter; activating Level One public health emergency response in all localities; the central government set up a leading group; classified management of "four categories of personnel"; launching makeshift hospitals; digital management for a matrix of urban communities; counterpart assistance. The following four factors were the key influencing factors of the cumulative confirmed cases in Singapore: The National Centre for Infectious Diseases screening center opens; border control measures; surveillance measures; Public Health Preparedness Clinics launched. CONCLUSIONS: Through analyzing the key epidemic prevention and control policies of the two countries, we found that the following factors are critical to combat COVID-19: active case detection, early detection of patients, timely isolation, and treatment, and increasing of medical capabilities. Countries should choose appropriate response strategies with health equity in mind to ultimately control effectively the spread of COVID-19 worldwide.

A statistical model for the dynamics of COVID-19 infections and their case detection ratio in 2020.

The case detection ratio of coronavirus disease 2019 (COVID-19) infections varies over time due to changing testing capacities, different testing strategies, and the evolving underlying number of infections itself. This note shows a way of quantifying these dynamics by jointly modeling the reported number of detected COVID-19 infections with nonfatal and fatal outcomes. The proposed methodology also allows to explore the temporal development of the actual number of infections, both detected and undetected, thereby shedding light on the infection dynamics. We exemplify our approach by analyzing German data from 2020, making only use of data available since the beginning of the pandemic. Our modeling approach can be used to quantify the effect of different testing strategies, visualize the dynamics in the case detection ratio over time, and obtain information about the underlying true infection numbers, thus enabling us to get a clearer picture of the course of the COVID-19 pandemic in 2020.

Understanding COVID-19 dynamics and the effects of interventions in the Philippines: A mathematical modelling study.

BACKGROUND: COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries, possibly because of differing demographics, socioeconomics, surveillance, and policy responses. Here, we investigate the role of multiple factors on COVID-19 dynamics in the Philippines, a LMIC that has had a relatively severe COVID-19 outbreak. METHODS: We applied an age-structured compartmental model that incorporated time-varying mobility, testing, and personal protective behaviors (through a "Minimum Health Standards" policy, MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon, Central Visayas, and the National Capital Region). We estimated effects of control measures, key epidemiological parameters, and interventions. FINDINGS: Population age structure, contact rates, mobility, testing, and MHS were sufficient to explain the Philippines epidemic based on the good fit between modelled and reported cases, hospitalisations, and deaths. The model indicated that MHS reduced the probability of transmission per contact by 13-27%. The February 2021 case detection rate was estimated at ~8%, population recovered at ~9%, and scenario projections indicated high sensitivity to MHS adherence. INTERPRETATION: COVID-19 dynamics in the Philippines are driven by age, contact structure, mobility, and MHS adherence. Continued compliance with low-cost MHS should help the Philippines control the epidemic until vaccines are widely distributed, but disease resurgence may be occurring due to a combination of low population immunity and detection rates and new variants of concern.

Non-intrusive wastewater surveillance for monitoring of a residential building for COVID-19 cases.

Wastewater-based surveillance for SARS-CoV-2 has been used for the early warning of transmission or objective trending of the population-level disease prevalence. Here, we describe a new use-case of conducting targeted wastewater surveillance to complement clinical testing for case identification in a small community at risk of COVID-19 transmission. On 2 July 2020, a cluster of COVID-19 cases in two unrelated households residing on different floors in the same stack of an apartment building was reported in Singapore. After cases were conveyed to healthcare facilities and six healthy household contacts were quarantined in their respective apartments, wastewater surveillance was implemented for the entire residential block. SARS-CoV-2 was subsequently detected in wastewaters in an increasing frequency and concentration, despite the absence of confirmed COVID-19 cases, suggesting the presence of fresh case/s in the building. Phone interviews of six residents in quarantine revealed that no one was symptomatic (fever/respiratory illness). However, when nasopharyngeal swabs from six quarantined residents were tested by PCR tests, one was positive for SARS-CoV-2. The positive case reported episodes of diarrhea and the case's stool sample was also positive for SARS-CoV-2, explaining the SARS-CoV-2 spikes observed in wastewaters. After the case was conveyed to a healthcare facility, wastewaters continued to yield positive signals for five days, though with a decreasing intensity. This was attributed to the return of recovered cases, who had continued to shed the virus. Our findings demonstrate the utility of wastewater surveillance as a non-intrusive tool to monitor high-risk COVID-19 premises, which is able to trigger individual tests for case detection, highlighting a new use-case for wastewater testing.

Routine saliva testing for the identification of silent coronavirus disease 2019 (COVID-19) in healthcare workers.

OBJECTIVE: Current COVID-19 guidelines recommend symptom-based screening and regular nasopharyngeal (NP) testing for healthcare personnel in high-risk settings. We sought to estimate case detection percentages with various routine NP and saliva testing frequencies. DESIGN: Simulation modeling study. METHODS: We constructed a sensitivity function based on the average infectiousness profile of symptomatic coronavirus disease 2019 (COVID-19) cases to determine the probability of being identified at the time of testing. This function was fitted to reported data on the percent positivity of symptomatic COVID-19 patients using NP testing. We then simulated a routine testing program with different NP and saliva testing frequencies to determine case detection percentages during the infectious period, as well as the presymptomatic stage. RESULTS: Routine biweekly NP testing, once every 2 weeks, identified an average of 90.7% (SD, 0.18) of cases during the infectious period and 19.7% (SD, 0.98) during the presymptomatic stage. With a weekly NP testing frequency, the corresponding case detection percentages were 95.9% (SD, 0.18) and 32.9% (SD, 1.23), respectively. A 5-day saliva testing schedule had a similar case detection percentage as weekly NP testing during the infectious period, but identified ~10% more cases (mean, 42.5%; SD, 1.10) during the presymptomatic stage. CONCLUSION: Our findings highlight the utility of routine noninvasive saliva testing for frontline healthcare workers to protect vulnerable patient populations. A 5-day saliva testing schedule should be considered to help identify silent infections and prevent outbreaks in nursing homes and healthcare facilities.

Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental model.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic began with a detected cluster of pneumonia cases in Wuhan, China in December 2019. Endemic transmission was recognized in Canada in early February 2020, making it urgent for public health stakeholders to have access to robust and reliable tools to support decision-making for epidemic management. The objectives of this paper are to present one of these tools-an aged-stratified dynamic compartmental model developed by the Public Health Agency of Canada in collaboration with Statistics Canada-and to model the impact of non-pharmaceutical interventions on the attack rate of COVID-19 infection in Canada. METHODS: This model simulates the impact of different levels of non-pharmaceutical interventions, including case detection/isolation, contact tracing/quarantine and changes in the level of physical distancing in Canada, as restrictive closures began to be lifted in May 2020. RESULTS: This model allows us to highlight the importance of a relatively high level of detection and isolation of cases, as well as tracing and quarantine of individuals in contact with those cases, in order to avoid a resurgence of the epidemic in Canada as restrictive closures are lifted. Some level of physical distancing by the public will also likely need to be maintained. CONCLUSION: This study underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public health to identify cases and trace contacts, and to encourage Canadians to get tested if they are at risk of having been infected and to maintain physical distancing in public areas.

Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria.

This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19.

COVID-19 in Singapore - a case series from primary care.

As the COVID-19 pandemic worsens, early case detection is vital to limiting community spread. We describe our experiences with four COVID-19 cases at the polyclinics in January and February 2020. This retrospective case series highlights the challenges primary care clinicians face in the early identification of suspect cases based on clinical criteria only. To improve case detection, clinicians can sharpen their clinical acumen by keeping abreast with the latest COVID-19 developments and by maintaining a high state of vigilance.