Surveillance System For Early Detection Research Articles

Integrating wastewater and randomised prevalence survey data for national COVID surveillance

During the COVID-19 pandemic, studies in a number of countries have shown how wastewater can be used as an efficient surveillance tool to detect outbreaks at much lower cost than traditional prevalence surveys. In this study, we consider the utilisation of wastewater data in the post-pandemic setting, in which collection of health data via national randomised prevalence surveys will likely be run at a reduced scale; hence an affordable ongoing surveillance system will need to combine sparse prevalence data with non-traditional disease metrics such as wastewater measurements in order to estimate disease progression in a cost-effective manner. Here, we use data collected during the pandemic to model the dynamic relationship between spatially granular wastewater viral load and disease prevalence. We then use this relationship to nowcast local disease prevalence under the scenario that (i) spatially granular wastewater data continue to be collected; (ii) direct measurements of prevalence are only available at a coarser spatial resolution, for example at national or regional scale. The results from our cross-validation study demonstrate the added value of wastewater data in improving nowcast accuracy and reducing nowcast uncertainty. Our results also highlight the importance of incorporating prevalence data at a coarser spatial scale when nowcasting prevalence at fine spatial resolution, calling for the need to maintain some form of reduced-scale national prevalence surveys in non-epidemic periods. The model framework is disease-agnostic and could therefore be adapted to different diseases and incorporated into a multiplex surveillance system for early detection of emerging local outbreaks.

First report of 'Candidatus Phytoplasma pruni' associated with X-disease on sweet cherry (Prunus avium L.) in Canada.

British Columbia (BC) is the lead producer of sweet cherries in Canada with more than 2,000 ha in production and a farm gate value of over CAD$100 million annually. Since 2010, an outbreak of little cherry disease caused by Little cherry virus 1 (LChV1) and Little cherry virus 2 (LChV2), as well as X-disease (XD) caused by 'Candidatus Phytoplasma pruni' has caused significant economic losses in neighboring Washington State (WA), USA. LChV1 and LChV2 have long been known to occur in BC (Theilmann et al. 2002); however, 'Ca. P. pruni' has not yet been reported in BC. Due to its geographical proximity to WA State, the BC cherry industry expressed significant concerns about the possible presence of the phytoplasma in cherry orchards. Accordingly, the main objective of this study was to survey cherry orchards to determine whether 'Ca. P. pruni' was present in symptomatic trees in BC. A total of 118 samples of leaves and fruit stems from individual symptomatic trees were collected prior to harvest from nine cherry orchards and one nectarine orchard in the Okanagan and Similkameen Valleys in BC. Characteristic symptoms included small and misshapen fruit with poor color development. Samples were submitted to AGNEMA, LLC (Pasco, WA) for testing using qPCR TaqMan assays for LChV1 (Katsiani et al. 2018), LChV2 (Shires et al. 2022) and 'Ca. P. pruni' (Kogej et al. 2020). Test results showed 21 samples (17.8%) from three cherry orchards positive for LChV2 and 2 samples (1.7%) from one cherry orchard positive for 'Ca. P. pruni'. In order to confirm the identification of 'Ca. P. pruni', part of the 16S ribosomal RNA gene was amplified by nested PCR using the P1/P7 followed by R16F2n/R2 primer sets (Gundersen and Lee 1996) and Sanger sequenced. BC-XD-Pa-1 (GenBank Acc. No. OR539920) and BC-XD-Pa-2 (OR537699) were identical to one another and showed 99.92% identity to the 'Ca. P. pruni' reference strain CX-95 (JQ044397). Analysis using iPhyClassifier (Zhou et al. 2009) indicated that they were 16SrIII-A strains. Interestingly, the two partial 16S sequences showed 100% nucleotide identity to strain 10324 (MH810016) and others from WA. For additional confirmation, partial secA (Hodgetts et al. 2008) and secY (Lee et al. 2010) translocases were amplified and sequenced. As with the 16S sequences, secY sequences (OR542980, OR542981) showed 99.92% nucleotide identity to strain CX-95 (JQ268249), and 100% to strain 10324 (MH810035). The secA sequences (OR542978, OR542979) had nucleotide identities of 99.77% to strain CX (MW547067), and 100% to the Green Valley strain from California (EU168733). Accordingly, 'Ca. P. Pruni' was confirmed to be present in sweet cherry samples from BC. 'Ca. P. Pruni'-related strains have been previously reported to occur in Canada in commercial poinsettias (Euphorbia pulcherrima) (Arocha-Rosete et al. 2021). To our knowledge, this is the first report of 'Ca. P. Pruni' in sweet cherry in Canada. Due to the important economic value of sweet cherries in BC, these findings are highly significant and represent the first steps towards the development of a surveillance system for early detection of XD, and consequent implementation of management strategies, including vector control. As required by federal and provincial regulations, cherry trees infected with LChV2 and 'Ca. P. Pruni' found in the survey were removed by the growers.

Poliovirus serological assay after the cVDPV1 outbreak in Papua New Guinea: a cross-sectional study from 2020 to 2021

In June 2018, a type 1 circulating vaccine-derived poliovirus (cVDPV1) outbreak was declared in Papua New Guinea (PNG), resulting in a total of 26 paralytic confirmed cases. Eight vaccination campaign rounds with bivalent oral poliovirus vaccine (bOPV) were carried out in response. Prevalence of neutralizing polio antibodies in children was assessed two years after the outbreak response was completed. We conducted a cross-sectional serological survey among children aged 6 months-10 years selected from six provinces in PNG to evaluate seroprevalence of neutralizing polio antibodies to the three poliovirus serotypes and analyse sociodemographic risk factors. We included 984 of 1006 enrolled children in the final analysis. The seroprevalence of neutralizing polio antibodies for serotype 1, 2 and 3 was 98.3% (95% CI: 97.4-98.9), 63.1% (95% CI: 60.1-66.1) and 95.0% (95% CI: 93.6-96.3), respectively. Children <1 year had significantly lower type 1 seroprevalence compared to older children (p<0.001); there were no significant differences in seroprevalence among provinces. PNG successfully interrupted transmission of cVDPV1 with several high coverage bOPV campaigns and seroprevalence remained high after two years. The emergence of cVDPV strains underscores the importance of maintaining high levels of routine immunization coverage and effective surveillance systems for early detection. World Health Organization through a Rotary International IPPC grant.

Threat of Antimicrobial Resistance among Pilgrims with Infectious Diseases during Hajj: Lessons Learnt from COVID-19 Pandemic.

Hajj pilgrimage is a large mass gathering global event that may facilitate the spread and emergence of various infectious diseases as well as antimicrobial resistance (AMR) in a local and global scenario. Planning and preparing for these public health issues is a challenging and complex process for the Kingdom of Saudi Arabia (KSA) health authorities. Despite multiple efforts for the prevention and treatment of infectious diseases through longtime funding in education and medical care, the prevalence of infectious disease is still high among Hajj pilgrims. The commonly observed infectious diseases during Hajj include respiratory tract infections (influenza and pneumonia), urinary tract infections and skin infections that may necessitate the use of antimicrobials. Beta-lactams are used as a first-line treatment for hospital acquired infections as well as community acquired infections due to their broad-spectrum activity. However, most of the bacterial isolates such as Staphylococcus spp., Pseudomonas spp. and E. coli are resistant to beta-lactams. Irrational use of antimicrobials, lack of infection prevention practices and suboptimal healthcare access further exacerbate the risk of spreading AMR among Hajj pilgrims. Enhanced collaboration between countries, sharing of best practices and international cooperation are crucial in addressing AMR threats among pilgrims. Consequently, robust surveillance systems for early detection and monitoring of AMR, collaboration with national as well as international healthcare agencies, effective infection prevention and control measures, public awareness and rational use of antimicrobials via antimicrobial stewardship programs are required to mitigate the risk of AMR and ensure the health and well-being of pilgrims during Hajj.

The burden of monkeypox virus amidst the Covid-19 pandemic in Africa: A double battle for Africa

The Coronavirus Disease - 19 (COVID-19) pandemic has put additional strain on Africa's fragile healthcare systems and has impacted the rise of emerging and re-emerging infectious diseases. Currently, there is a rise in cases of Monkeypox Disease, a zoonotic viral disease caused by the Monkeypox virus, which was first documented in 1970 in the Democratic Republic of the Congo. Most of the clinical symptoms of Monkeypox resemble that of smallpox, whose virus also belongs to the same genus. Initial symptoms include headache, fever, and fatigue, followed by lymphadenopathy and a rash. This study aims to provide more insight into Monkeypox by exposing its current burden and efforts to combat it amidst COVID-19 in Africa. Since Monkeypox disease is re-emerging and is less contagious than COVID-19, prevention and treatment are much more manageable. Still, African countries face several crucial challenges in responding to the Monkeypox in times of the covid-19 pandemic. These include lack of a well-functioning surveillance system for early detection of the disease, lack of awareness and knowledge of the monkeypox disease across the general population, lack of healthcare facilities already burdened by COVID-19 cases, and shortage of trained healthcare professionals.On the other hand, one significant factor contributing to the minimized risk in Africa was the smallpox vaccination done before 1980. However, a declining cross-protective immunity is seen in those inoculated with the smallpox vaccine and the ever-increasing risk to the unvaccinated population. Thus, focusing on vaccination and disease surveillance operations and diligent monitoring, as well as cross-border collaborations with international sectors, including One Health, FOA, OIE, and WHO is critical to achieving the ultimate eradication of monkeypox in Africa.

The Prevalence of Psychological Stress and Its Associated Factors among Secondary School Teachers in Samarahan and Asajaya District

A wide range of occupations have been associated with psychological stress, and the teaching profession has been considered as one of the most stressful jobs. This study aimed to determine the prevalence of psychological stress and its associated factors among secondary school teachers. A cross-sectional study was conducted among secondary school teachers in Samarahan and Asajaya districts using selfadministered questionnaires. The status of psychological stress was measured using the Malay version of DASS-21. The Teachers Stress Inventory was adapted to identify the psychosocial factors. The overall prevalence of psychological stress from this study was 19.5%. Out of 241 teachers, 9.1% had mild stress, 7.1% had moderate stress, and 3.3% had severe to very severe stress. The prevalence of psychological stress was significant among younger teachers, single, divorced or widowed, and those with the least household income. Among occupational factors, only the number of years of teaching experience has a significant relationship with psychological stress. The logistic regression analysis identified four significant elements associated with psychological stress, notably household income, anxiety, depression and time management. As a conclusion, the burden of psychological stress among school teachers can be associated with either individual factors or work-related factors. The responsibility in managing mental health among teachers does not only lie with the individual but at every level in the organisation. The surveillance systems for early detection of psychological stress can be implemented at the school level.

Epidemiology of Diphtheria in Yemen, 2017-2018: Surveillance Data Analysis.

BackgroundAs a consequence of war and the collapse of the health system in Yemen, which prevented many people from accessing health facilities to obtain primary health care, vaccination coverage was affected, leading to a deadly diphtheria epidemic at the end of 2017.ObjectiveThis study aimed to describe the epidemiology of diphtheria in Yemen and determine its incidence and case fatality rate.MethodsData were obtained from the diphtheria surveillance program 2017-2018, using case definitions of the World Health Organization. A probable case was defined as a case involving a person having laryngitis, pharyngitis, or tonsillitis and an adherent membrane of the tonsils, pharynx, and/or nose. A confirmed case was defined as a probable case that was laboratory confirmed or linked epidemiologically to a laboratory-confirmed case. Data from the Central Statistical Organization was used to calculate the incidence per 100,000 population. A P value <.05 was considered significant.ResultsA total of 2243 cases were reported during the period between July 2017 and August 2018. About 49% (1090/2243, 48.6%) of the cases were males. About 44% (978/2243, 43.6%) of the cases involved children aged 5 to 15 years. Respiratory tract infection was the predominant symptom (2044/2243, 91.1%), followed by pseudomembrane (1822/2243, 81.2%). Based on the vaccination status, the percentages of partially vaccinated, vaccinated, unvaccinated, and unknown status patients were 6.6% (148/2243), 30.8% (690/2243), 48.6% (10902243), and 14.0% (315/2243), respectively. The overall incidence of diphtheria was 8 per 100,000 population. The highest incidence was among the age group <15 years (11 per 100,000 population), and the lowest incidence was among the age group ≥15 years (5 per 100,000 population). The overall case fatality rate among all age groups was 5%, and it was higher (10%) in the age group <5 years. Five governorates that were difficult to access (Raymah, Abyan, Sa'ada, Lahj, and Al Jawf) had a very high case fatality rate (22%).ConclusionsDiphtheria affected a large number of people in Yemen in 2017-2018. The majority of patients were partially or not vaccinated. Children aged ≤15 years were more affected, with higher fatality among children aged <5 years. Five governorates that were difficult to access had a case fatality rate twice that of the World Health Organization estimate (5%-10%). To control the diphtheria epidemic in Yemen, it is recommended to increase routine vaccination coverage and booster immunizations, increase public health awareness toward diphtheria, and strengthen the surveillance system for early detection and immediate response.

UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance.

In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aerial, ground and marine unmanned vehicles with important features such as prioritising early detections and success rate. A new Competitive Coevolutionary Genetic Algorithm (CompCGA) is proposed to optimise the vehicles’ parameters and escapers’ evasion ability using a predator-prey approach. Our results show that CROMM-MS is not only viable for surveillance tasks but also that its results are competitive in regard to the state-of-the-art approaches.

Opportunities and Challenges for Developing Syndromic Surveillance Systems for the Detection of Social Epidemics.

This commentary explores the potential and challenges of developing syndromic surveillance systems with the ability to more rapidly detect epidemics of addiction, poverty, housing instability, food insecurity, social isolation and other social determinants of health (SDoH). Epidemiologists tracking SDoH heavily rely on expensive government surveys released annually, delaying for months if not years the timely detection of social epidemics, defined as sudden, rapid or unexpected changes in social determinants of population health. Conversely, infectious disease syndromic surveillance is an effective early warning tool for epidemic diseases using various types of non-traditional epidemiological data from emergency room chief complaints to search query data. Based on such experience, novel social syndromic surveillance systems for early detection of social epidemics with health implications are not only possible but necessary. Challenges to their widespread implementation include incorporating disparate proprietary data sources and database integration. Significantly more resources are critically needed to address these barriers to allow for accessing, integrating and rapidly analyzing appropriate data streams to make syndromic surveillance for social determinants of health widely available to public health professionals.

The Impact of Mass Gatherings on Emergency Department Patient Presentations with Communicable Diseases Related to Syndromic Indicators: An Integrative Review.

Mass-gathering events (MGEs) are commonly associated with a higher than average rate of morbidity. Spectators, workers, and the substantial number of MGE attendees can increase the spread of communicable diseases. During an MGE, emergency departments (EDs) play an important role in offering health care services to both residents of the local community and event attendees. Syndromic indicators (SIs) are widely used in an ED surveillance system for early detection of communicable diseases. This literature review aimed to develop an understanding of the effect of MGEs on ED patient presentations with communicable diseases and their corresponding SIs. An integrative literature review methodology was used. Online databases were searched to retrieve relevant academic articles that focused on MGEs, EDs, and SIs. Inclusion/exclusion criteria were applied to screen articles. The Standard Quality Assessment Criteria for Evaluating Primary Research (QualSyst) assessment tool was used to assess the quality of included papers. Eleven papers were included in this review; all discussed the impact of an MGE on patient presentations with communicable diseases at EDs/hospitals. Most included studies used the raw number of patients who presented or were admitted to EDs/hospitals to determine impact. Further, the majority of studies focused on either respiratory infections (n = 4) or gastrointestinal infections (n = 2); two articles reported on both. Eight articles mentioned SIs; however, such information was limited. The quality of evidence (using QualSyst) ranged from 50% to 90%. Limited research exists on the impact of MGEs on ED presentations with communicable diseases and related SIs. Recommendations for future MGE studies include assessing differences in ED presentations with communicable diseases regarding demographics, clinical characteristics, and outcomes before, during, and after the event. This would benefit health care workers and researchers by offering more comprehensive knowledge for application into practice.

Multivariate syndromic surveillance for cattle diseases: Epidemic simulation and algorithm performance evaluation

Multivariate Syndromic Surveillance (SyS) systems that simultaneously assess and combine information from different data sources are especially useful for strengthening surveillance systems for early detection of infectious disease epidemics. Despite the strong motivation for implementing multivariate SyS and there being numerous methods reported, the number of operational multivariate SyS systems in veterinary medicine is still very small. One possible reason is that assessing the performance of such surveillance systems remains challenging because field epidemic data are often unavailable. The objective of this study is to demonstrate a practical multivariate event detection method (directionally sensitive multivariate control charts) that can be easily applied in livestock disease SyS, using syndrome time series data from the Swiss cattle population as an example. We present a standardized method for simulating multivariate epidemics of different diseases using four diseases as examples: Bovine Virus Diarrhea (BVD), Infectious Bovine Rhinotracheitis (IBR), Bluetongue virus (BTV) and Schmallenberg virus (SV). Two directional multivariate control chart algorithms, Multivariate Exponentially Weighted Moving Average (MEWMA) and Multivariate Cumulative Sum (MCUSUM) were compared. The two algorithms were evaluated using 12 syndrome time series extracted from two Swiss national databases. The two algorithms were able to detect all simulated epidemics around 4.5 months after the start of the epidemic, with a specificity of 95%. However, the results varied depending on the algorithm and the disease. The MEWMA algorithm always detected epidemics earlier than the MCUSUM, and epidemics of IBR and SV were detected earlier than epidemics of BVD and BTV. Our results show that the two directional multivariate control charts are promising methods for combining information from multiple time series for early detection of subtle changes in time series from a population without producing an unreasonable amount of false alarms. The approach that we used for simulating multivariate epidemics is relatively easy to implement and could be used in other situations where real epidemic data are unavailable. We believe that our study results can support the implementation and assessment of multivariate SyS systems in animal health.

Flexibility of ED surveillance system to monitor dengue outbreak in Reunion Island

Flexibility of ED surveillance system to monitor dengue outbreak in Reunion Island

Optimising the seasonal deployment of surveillance traps for detection of incipient pest invasions

Early detection of biological invasions is necessary to enable successful management responses, such as containment and eradication. Several nations operate risk-based surveillance systems for early detection and proof of freedom from economically damaging pests and diseases. Identifying the best times of year to deploy and remove surveillance traps is important for maximising the probability of detection while minimising the economic costs of large-scale trapping.We modelled seasonal population dynamics to identify which days of the year contribute most to surveillance sensitivity and therefore the appropriate trapping period, and applied this to trapping for fruit flies (Diptera: Tephritidae) in New Zealand. Optimum trapping periods were defined as the minimum contiguous dates which would give a specific proportion (80%, 90%, 95%, or 99%) of the probability of detection compared to year-round trapping. Seasonal dynamics were based on an empirical model for the effect of temperature on population increase and decline, fitted to published data from around the world. The model suggested Mediterranean fruit fly (Medfly) should be trapped in the upper half of the North Island from at least November through May. Additional trapping in October and June may be warranted in the far north. Favourable microclimates or climate change to 2040 may allow Medfly populations to establish as far south as Christchurch and Alexandra, where trapping should run from mid December to early May. Queensland fruit fly (Qfly) and oriental fruit fly were unlikely to establish south of Napier and optimum trapping times for these species are approximately mid November through May. Climate change under moderate scenarios is unlikely to significantly alter the optimum trapping periods until at least 2040.The results were not sensitive to assumptions about trap efficacy and founder population size. However, they are based on simplified relationships between the intrinsic rate of increase and temperature. This approach is applicable to any invasive species with seasonal variation in surveillance efficacy. In response to this work, New Zealand's biosecurity authority has changed the seasonal timing of their fruit fly trapping to optimise detection efficacy.

Molecular assays for antimalarial drug resistance surveillance: A target product profile.

Antimalarial drug resistance is a major constraint for malaria control and elimination efforts. Artemisinin-based combination therapy is now the mainstay for malaria treatment. However, delayed parasite clearance following treatment with artemisinin derivatives has now spread in the Greater Mekong Sub region and may emerge or spread to other malaria endemic regions. This spread is of great concern for malaria control programmes, as no alternatives to artemisinin-based combination therapies are expected to be available in the near future. There is a need to strengthen surveillance systems for early detection and response to the antimalarial drug resistance threat. Current surveillance is mainly done through therapeutic efficacy studies; however these studies are complex and both time- and resource-intensive. For multiple common antimalarials, parasite drug resistance has been correlated with specific genetic mutations, and the molecular markers associated with antimalarial drug resistance offer a simple and powerful tool to monitor the emergence and spread of resistant parasites. Different techniques to analyse molecular markers associated with antimalarial drug resistance are available, each with advantages and disadvantages. However, procedures are not adequately harmonized to facilitate comparisons between sites. Here we describe the target product profiles for tests to analyse molecular markers associated with antimalarial drug resistance, discuss how use of current techniques can be standardised, and identify the requirements for an ideal product that would allow malaria endemic countries to provide useful spatial and temporal information on the spread of resistance.

Chikungunya outbreak (2017) in Bangladesh: Clinical profile, economic impact and quality of life during the acute phase of the disease.

BackgroundChikungunya virus causes mosquito-transmitted infection that leads to extensive morbidity affecting substantial quality of life. Disease associated morbidity, quality of life, and financial loss are seldom reported in resources limited countries, such as Bangladesh. We reported the acute clinical profile, quality of life and consequent economic burden of the affected individuals in the recent chikungunya outbreak (May to September 2017) in Dhaka city, Bangladesh.MethodsWe conducted a cross-sectional study during the peak of chikungunya outbreak (July 24 to August 5, 2017) to document the clinical profiles of confirmed cases (laboratory test positive) and probable cases diagnosed by medical practitioners. Data related to clinical symptoms, treatment cost, loss of productivity due to missing work days, and quality of life during their first two-weeks of symptom onset were collected via face to face interview using a structured questionnaire. World Health Organization endorsed questionnaire was used to assess the quality of life.ResultsA total of 1,326 chikungunya cases were investigated. Multivariate analysis of major clinical variables showed no statistically significant differences between confirmed and probable cases. All the patients reported joint pain and fever. Other more frequently reported symptoms include headache, loss of appetite, rash, myalgia, and itching. Arthralgia was polyarticular in 56.3% of the patients. Notably, more than 70% patients reported joint pain as the first presenting symptom. About 83% of the patients reported low to very low overall quality of life. Nearly 30% of the patients lost more than 10 days of productivity due to severe arthropathy.ConclusionsThis study represents one of the largest samples studied so far around the world describing the clinical profile of chikungunya infection. Our findings would contribute to establish an effective syndromic surveillance system for early detection and timely public health intervention of future chikungunya outbreaks in resource-limited settings like Bangladesh.

Alternative to plating for calcaneal fracture treatment via sinus tarsi approach

Currently in China, the schistosomiasis control program has shifted its focus from transmission control to the elimination of the disease. Effective forecast and surveillance systems of schistiosomiasis are of great importance for issuing timely and early warnings on risk of infection, and therefore implementing preventive measures to avoid infection. There is great demand in more sensitive and specific methods to improve the surveillance system for early detection of S. japonicum infection in sentinel mice. In this study, we reported a sensitive nested-PCR assay targeting a 303-bp fragment from highly repetitive retrotransposon SjCHGCS19 to detect the S. japonicum DNA in sera of experimental mice. Meanwhile, detection efficacy of the nested-PCR was compared with two conventional methods for field monitoring schistosomiasis such as ELISA and IHA. The nested-PCR assay could detect the specific DNA at 3-day post-infection in sera of mice with 5 cercariae infection, while for ELISA and IHA, both show negative results even after 2 weeks post-infection in mice with 20 cercariae infection. Our results demonstrated the DNA-based assay was more sensitive to make early diagnosis of S. japonicum infection in sentinel mice models, which will improve the early-warning ability of schistosomiasis surveillance system.

Optimizing sentinel surveillance in temporal network epidemiology

To help health policy makers gain response time to mitigate infectious disease threats, it is essential to have an efficient epidemic surveillance. One common method of disease surveillance is to carefully select nodes (sentinels, or sensors) in the network to report outbreaks. One would like to choose sentinels so that they discover the outbreak as early as possible. The optimal choice of sentinels depends on the network structure. Studies have addressed this problem for static networks, but this is a first step study to explore designing surveillance systems for early detection on temporal networks. This paper is based on the idea that vaccination strategies can serve as a method to identify sentinels. The vaccination problem is a related question that is much more well studied for temporal networks. To assess the ability to detect epidemic outbreaks early, we calculate the time difference (lead time) between the surveillance set and whole population in reaching 1% prevalence. We find that the optimal selection of sentinels depends on both the network’s temporal structures and the infection probability of the disease. We find that, for a mild infectious disease (low infection probability) on a temporal network in relation to potential disease spreading (the Prostitution network), the strategy of selecting latest contacts of random individuals provide the most amount of lead time. And for a more uniform, synthetic network with community structure the strategy of selecting frequent contacts of random individuals provide the most amount of lead time.

The Evolution of BioSense: Lessons Learned and Future Directions.

The BioSense program was launched in 2003 with the aim of establishing a nationwide integrated public health surveillance system for early detection and assessment of potential bioterrorism-related illness. The program has matured over the years from an initial Centers for Disease Control and Prevention-centric program to one focused on building syndromic surveillance capacity at the state and local level. The uses of syndromic surveillance have also evolved from an early focus on alerts for bioterrorism-related illness to situational awareness and response, to various hazardous events and disease outbreaks. Future development of BioSense (now the National Syndromic Surveillance Program) includes, in the short term, a focus on data quality with an emphasis on stability, consistency, and reliability and, in the long term, increased capacity and innovation, new data sources and system functionality, and exploration of emerging technologies and analytics.

Early detection of circulating DNA of Schistosoma japonicum in sentinel mice models

Currently in China, the schistosomiasis control program has shifted its focus from transmission control to the elimination of the disease. Effective forecast and surveillance systems of schistiosomiasis are of great importance for issuing timely and early warnings on risk of infection, and therefore implementing preventive measures to avoid infection. There is great demand in more sensitive and specific methods to improve the surveillance system for early detection of S. japonicum infection in sentinel mice. In this study, we reported a sensitive nested-PCR assay targeting a 303-bp fragment from highly repetitive retrotransposon SjCHGCS19 to detect the S. japonicum DNA in sera of experimental mice. Meanwhile, detection efficacy of the nested-PCR was compared with two conventional methods for field monitoring schistosomiasis such as ELISA and IHA. The nested-PCR assay could detect the specific DNA at 3-day post-infection in sera of mice with 5 cercariae infection, while for ELISA and IHA, both show negative results even after 2 weeks post-infection in mice with 20 cercariae infection. Our results demonstrated the DNA-based assay was more sensitive to make early diagnosis of S. japonicum infection in sentinel mice models, which will improve the early-warning ability of schistosomiasis surveillance system.

Predictors of Neonatal Tetanus Mortality in Katsina State, Northwestern Nigeria.

Background:The mortality rate of neonatal tetanus (NNT) remains high in Nigeria. The study was guided by Mosley and Chen’s model for the elements of child survival in developing countries. The goal of the study was to assess the associations between selected NNT risk factors, number of maternal tetanus toxoid injections, frequency of antenatal visits, place of delivery, and cord care with neonatal mortality as the outcome variable.Methods:The study is a retrospective record review using data from 332 NNT records and analyzed using a logistic regression model.Findings:Neonates whose mothers had 1 dose of tetanus toxoid vaccine were found to be 4% less prone to NNT mortality compared to neonates whose mothers did not have any dose of tetanus toxoid vaccine during pregnancy (P < .05, odds ratio = 4.12, 95% confidence interval = 1.04-16.29. Frequency of antenatal visits, place of delivery, and cord care were all not significant predictors of NNT mortality.Conclusion:The study shows that there is association between NNT risk factors and neonatal mortality, hence the need to further strengthen the NNT surveillance system for early detection of potential risk factors. This would help develop specific public health interventions aimed at improving the outcome of NNT.Implications:The identification and analysis of NNT mortality risk factors and promoting tetanus toxoid vaccination among pregnant women are effective strategies toward attaining NNT elimination goals in Nigeria.