Surveillance Coverage Research Articles

Laboratory surveillance for SARS-CoV-2 in India: Performance of testing & descriptive epidemiology of detected COVID-19, January 22 - April 30, 2020.

Background & objectives:India has been reporting the cases of coronavirus disease 2019 (COVID-19) since January 30, 2020. The Indian Council of Medical Research (ICMR) formulated and established laboratory surveillance for COVID-19. In this study, an analysis of the surveillance data was done to describe the testing performance and descriptive epidemiology of COVID-19 cases by time, place and person.Methods:The data were extracted from January 22 to April 30, 2020. The frequencies of testing performance were described over time and by place. We described cases by time (epidemic curve by date of specimen collection; seven-day moving average), place (area map) and person (attack rate by age, sex and contact status), and trends were represented along with public health measures and events.Results:Between January 22 and April 30, 2020, a total of 1,021,518 individuals were tested for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Testing increased from about 250 individuals per day in the beginning of March to 50,000 specimens per day by the end of April 2020. Overall, 40,184 (3.9%) tests were reported positive. The proportion of positive cases was highest among symptomatic and asymptomatic contacts, 2-3-fold higher than among those with severe acute respiratory infection, or those with an international travel history or healthcare workers. The attack rate (per million) by age was highest among those aged 50-69 yr (63.3) and was lowest among those under 10 yr (6.1). The attack rate was higher among males (41.6) than females (24.3). The secondary attack rate was 6.0 per cent. Overall, 99.0 per cent of 736 districts reported testing and 71.1 per cent reported COVID-19 cases.Interpretation & conclusions:The coverage and frequency of ICMR's laboratory surveillance for SARS-CoV-2 improved over time. COVID-19 was reported from most parts of India, and the attack rate was more among men and the elderly and common among close contacts. Analysis of the data indicates that for further insight, additional surveillance tools and strategies at the national and sub-national levels are needed.

某型无人机群的监视覆盖任务航路规划

某型无人机群的监视覆盖任务航路规划

Antimicrobial resistance in a war-torn country: Lessons learned in the Eastern Democratic Republic of the Congo

There is no doubt that antibiotics have reduced the burden of bacterial infectious diseases. Antimicrobial resistance threatens the effectiveness of successful treatment of infections and constitutes a public health concern with national and global dimensions. This problem is worrisome in war-torn areas like the Eastern Democratic Republic of the Congo. The difficulties experienced by war-torn nations in addressing antimicrobial resistance are significant for the rest of the globe as microbes do not acknowledge boundaries and do not distinguish between peace and wartime. In this paper, we describe the impact of warfare on the social determinants of health, the environment and biodiversity, and its consequences on the antibiotic use and the host-pathogen interplay. Furthermore, we describe different pillars to be taken into account, learned in a war-torn area, in combating antimicrobial resistance. These lessons are summarized in terms of tools to be used for combating antimicrobial resistance, challenges to overcome in war-torn setting and core actions to be undertaken. Surveillance is a valuable tool to combat antimicrobial resistance as it helps to detect resistant bacteria, enables correct decisions to be taken, guides policy recommendations and tracks the antibiotic use and misuse. The challenges encountered in this region include the shortage of competent laboratories, poor infrastructure and data management, lack of standard protocols, low coverage of surveillance, lack of intersectoral cooperation, and inadequate national, regional and international collaboration. Regarding this situation, the core actions to be undertaken include the establishment of ABR surveillance and monitoring systems, building laboratory capacity for rapid and reliable diagnostic testing, and engagement in national, regional and global surveillance networks. Therefore, this study showed an urgent need for establishing and implementing sentinel site surveillance laboratories and elaborating and implementing national action plans for combating antimicrobial resistance.

Measles Virus Infection and Immunity in a Suboptimal Vaccination Coverage Setting.

Despite efforts to improve surveillance and vaccination coverage, measles virus (MeV) continues to cause outbreaks also in high-income countries. As the reference laboratory of the Veneto Region, Italy, we analyzed changes in population immunity, described measles outbreaks, investigated MeV genetic diversity, and evaluated cross-protection of measles vaccination against MeV epidemic strains. Like most European areas, the Veneto Region has suboptimal measles vaccination coverage and is facing a growing public mistrust of vaccination. A progressive decline of measles vaccine uptake was observed during the last decade in the Veneto Region, leading to immunity gaps in children and young adults. Measles outbreaks were caused by the same MeV genotype B3, D4, and D8 strains that were circulating in other European countries. Eleven cases of measles were observed in immunized subjects. These cases were not associated with particular MeV genotypes nor with mutations in epitopes recognized by neutralizing antibodies. Accordingly, sera from fully vaccinated subjects cross-neutralized epidemic MeV strains, including the genotypes B3, D4, and D8, with the same high efficiency demonstrated against the vaccine strain. In fully vaccinated subjects, high MeV IgG antibody titers persisted up to 30 years following vaccination. These results support the use of the current measles-containing vaccines and strategies to strengthen vaccination.

Real-time high-resolution omnidirectional imaging platform for drone detection and tracking

Drones have become steadily affordable, which raises privacy and security concerns as well as interest in drone detection systems. On the other hand, drone detection is a challenging task due to small dimensions of drones, difficulty of long-distance detection, strict real-time constraints and necessity of wide angle coverage for drones. Although different radar and audio-assisted drone detection systems have been presented, they suffer from the cost, range, or interference problems. On the contrary, a long-range detection can be obtained by a vision-based system. Aiming that, we propose a real-time moving object detection and tracking system optimized for drone detection using 16 cameras with 20 MP resolution. The proposed system detects drones from short range and long range with 360\(^{\circ }\) surveillance coverage owing high-performance ultra-high-resolution (320 MP) video-processing capability. It is able to detect drones with 100 cm diameter from 700 m distance despite deceptive background. It is interference free, so multiple systems can properly operate in the vicinity without effecting each other. It integrates processing power of embedded systems with flexibility of software to generate a full platform for drone detection and tracking.

Strengthening surveillance systems for malaria elimination: a global landscaping of system performance, 2015\u20132017

BackgroundSurveillance is a core component of an effective system to support malaria elimination. Poor surveillance data will prevent countries from monitoring progress towards elimination and targeting interventions to the last remaining at-risk places. An evaluation of the performance of surveillance systems in 16 countries was conducted to identify key gaps which could be addressed to build effective systems for malaria elimination.MethodsA standardized surveillance system landscaping was conducted between 2015 and 2017 in collaboration with governmental malaria programmes. Malaria surveillance guidelines from the World Health Organization and other technical bodies were used to identify the characteristics of an optimal surveillance system, against which systems of study countries were compared. Data collection was conducted through review of existing material and datasets, and interviews with key stakeholders, and the outcomes were summarized descriptively. Additionally, the cumulative fraction of incident infections reported through surveillance systems was estimated using surveillance data, government records, survey data, and other scientific sources.ResultsThe landscaping identified common gaps across countries related to the lack of surveillance coverage in remote communities or in the private sector, the lack of adequate health information architecture to capture high quality case-based data, poor integration of data from other sources such as intervention information, poor visualization of generated information, and its lack of availability for making programmatic decisions. The median percentage of symptomatic cases captured by the surveillance systems in the 16 countries was estimated to be 37%, mostly driven by the lack of treatment-seeking in the public health sector (64%) or, in countries with large private sectors, the lack of integration of this sector within the surveillance system.ConclusionsThe landscaping analysis undertaken provides a clear framework through which to identify multiple gaps in current malaria surveillance systems. While perfect systems are not required to eliminate malaria, closing the gaps identified will allow countries to deploy resources more efficiently, track progress, and accelerate towards malaria elimination. Since the landscaping undertaken here, several countries have addressed some of the identified gaps by improving coverage of surveillance, integrating case data with other information, and strengthening visualization and use of data.

Improved capacity for influenza surveillance in the WHO Eastern Mediterranean Region: Progress in a challenging setting

BackgroundThe World Health Organization Regional Office for Eastern Mediterranean has partnered with the United States Centers for Disease Control and Prevention (CDC) to strengthen pandemic influenza preparedness and response in the Region since 2006. This partnership focuses on pandemic preparedness planning, establishing and enhancing influenza surveillance systems, improving laboratory capacity for detection of influenza viruses, estimating the influenza disease burden, and providing evidence to support policies for the introduction and increased use of seasonal influenza vaccines. MethodsVarious published and unpublished data from public and WHO sources, programme indicators of the CDC cooperative agreement and Pandemic Influenza Preparedness Framework were reviewed and analysed. Analyses and review of the programme indicators and published articles enabled us to generate information that was unavailable from only WHO sources. ResultsMost (19/22) countries of the Region have established influenza surveillance system; 16 countries in the Region have designated National Influenza Centres. The Region has seen considerable improvement in geographic coverage of influenza surveillance and influenza detection. Virus sharing has improved and almost all of the participating laboratories have achieved a 100% efficiency score in the WHO external quality assessment programme. At least seven countries have estimated their influenza disease burden using surveillance data and at least 17 are now using seasonal influenza vaccines as a control strategy for influenza illness. ConclusionThe Region has achieved substantial progress in surveillance and response to seasonal influenza, despite the adverse effects to the health systems of many countries due to acute and protracted emergencies and other significant challenges.

Incidence estimation from sentinel surveillance data; a simulation study and application to data from the Belgian laboratory sentinel surveillance

BackgroundInverse probability weighting (IPW) methods can be used to estimate the total number of cases from the sample collected through sentinel surveillance. Central to these methods are the inverse weights which can be derived in several ways and, in this case, represent the probability that laboratory (lab) sentinel surveillance detects a lab-confirmed case.MethodsWe compare different weights in a simulation study. Weights are obtained from the proportion of participating labs over all labs. We adjust these weights for attractiveness and density of labs over population. The market share of sentinel labs, as estimated by the econometric Huff-model, is also considered. Additionally, we investigate the effect of not recognizing sentinel labs as sentinel labs when they report no cases. We estimate the bias associated with the different weights as the difference between the simulated number of cases and the estimate of this total from the sentinel sample.As motivating data examples, we apply an extended Huff-model to four pathogens under laboratory sentinel surveillance in Belgium between 2010 and 2015 and discuss the model fit. We estimate the total number of lab-confirmed cases associated with Rotavirus, influenza virus, Y. enterocolitica and Campylobacter spp.. The extended Huff-model takes the lab-concept, the number of reimbursements and the number of departments, lab-density, regional borders, distance and competition between labs in account.ResultsEstimates obtained with the Huff-model were most accurate in the more complex simulation scenarios as compared to other weights. In the data examples, several significant coefficients are identified, but the fit of the Huff-model to the Belgian sentinel surveillance data leaves much variability in market shares unexplained.ConclusionThe Huff-model allows for estimation of the spatial and population coverage of sentinel surveillance and through IPW-methods also for the estimation of the total number of cases. The Huff-model‘s gravity function allows us to differentiate inside an area while estimating from the full dataset. Our data examples show that additional data on the participation to surveillance and practices of labs is necessary for a more accurate estimation.

Sero-prevalence of Rubella Antibodies in Pregnant Women with Bad Obstetric History Attending A Rural Tertiary Care Hospital in West Bengal, India

Background: Rubella infection in pregnant mothers is of great concern as it acts as a teratogen causing abortions, still births, intra-uterine foetal deaths and multiple birth defects. In India, rubella causes significant bad obstetric pregnancy outcome including congenital deformities due to lack of proper surveillance and immunization coverage with rubella vaccination. Aim: To determine Sero-prevalence of rubella IgM and IgG antibodies in Bad Obstetric History (BOH) pregnant women in Tertiary Rural Medical College in Eastern India. Materials and Methods: Cross sectional study was conducted from 1st January 2017 to 31st March 2017 on sera of 100 antenatal mothers with bad obstetric history aged between 20-40 years of age group with pregnancy of ≥18 wks. Rubella IgM and IgG antibodies were assessed by ELISA. Statistical Analysis: Percentage, proportions and ᵡ2 test were applied. Results: Eleven per cent (11%) sero-prevalence for IgM antibodies and 54% for IgG antibodies was observed with maximum sero-positivity among 20-25 years mothers. Repeated abortions were the commonest pregnancy outcome. Conclusion: All antenatal cases should be routinely screened for rubella, so that early diagnosis will help in proper management and foetal outcome and strong recommendation for universal coverage of MMR in early age group of children.

Integrating Phylodynamic Techniques for Next-generation HIV Surveillance in Florida

ObjectiveWe aim to 1) develop and implement a novel theoretical and technical framework able to dynamically model HIV transmission clusters in near-real time; 2) validate the model with real data; and 3) host focus groups with governmental stakeholders to identify optimal strategies for precision public health interventions.IntroductionReducing HIV incidence requires a ‘precision public health’ approach encompassing prevention campaigns, targeted interventions, and ‘next-generation’ surveillance through multimodal instruments, including sequencing. Molecular epidemiology methods (phylogenetics and phylodynamics) have recently gained traction for use in identifying and tracking epidemic transmission clusters, as well as reconstructing the demographic history of viral pathogen populations. However, such methods are not equipped to identify both transmission clusters and their corresponding dynamics in real time, and transmission clusters are assumed to be unrealistically static over the course of the epidemic. We will focus on the ongoing HIV epidemic in Florida, which has one of the highest HIV incidence rates in the United States. Although key HIV transmission risk groups have been identified in Florida through classical epidemiology surveillance methods, there remains a critical need for detection and tracking of expanding transmission clusters in near-real time.MethodsWe propose to develop and test a new phylodynamic method, HIV Dynamic Identification of Transmission Epicenters (HIV-DYNAMITE), that will support existing HIV surveillance efforts. In collaboration with the Florida Department of Health (FDOH), we will leverage an existing dataset, which contains over 44,300 sequences, and apply HIV-DYNAMITE to identify transmission clusters and infer growth trends of these clusters within epidemics. HIV-DYNAMITE will also be used to identify and predict infection trends and virus spread by conferring with demographic data. The system will be validated using newly obtained longitudinal data. Focus group discussions with the FDOH, the Centers for Disease Control and Prevention (CDC), and other stakeholders will be conducted to confer how to employ HIV-DYNAMITE into statewide informatics systems and to design future intervention strategies.ResultsThese methods are still under development.ConclusionsIn conclusion, this study aims to both complement and enhance existing efforts, such as the CDC’s HIV-TRACE, which is currently based on sequence data alone and lacks dynamic or geographic spread components. This approach has the potential to be incorporated into other settings within the US with comparable statewide surveillance and virus sequencing coverage through national reference centers.

Evaluation of a hospital-based injury surveillance system for monitoring road traffic deaths in Phuket, Thailand

Objectives: The objective of this study was to evaluate and injury surveillance (IS) system’s ability to monitor road traffic deaths and the coverage of road traffic injury and death surveillance in Phuket, Thailand.Methods: U.S. Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to qualitatively and quantitatively evaluate IS. Interviews with key stakeholders focused on IS’s usefulness, simplicity, flexibility, acceptability, and stability. Active case finding of 2014 road traffic deaths in all paper and electronic hospital record systems was used to assess system sensitivity, positive predictive value, and data quality. Electronic data matching software was used to determine the implications of combining IS data with other provincial-level data sources (e.g., death certificates, electronic vehicle insurance claim system).Results: Evaluation results indicated that IS was useful, flexible, acceptable, and stable, with a high positive predictive value (99%). Simplicity was limited due to the burden of collecting data on all injuries and use of paper-based data collection forms. Sensitivity was low, with IS only identifying 55% of hospital road traffic death cases identified during active case finding; however, IS cases were representative of cases identified. Data accuracy and completeness varied across data fields. Combining IS with active case finding, death certificates, and the electronic vehicle insurance claim system more than doubled the number of road traffic death cases identified in Phuket.Conclusion: An efficient and comprehensive road traffic injury and death surveillance system is critical for monitoring Phuket’s road traffic burden. The hospital-based IS system is a useful system for monitoring road traffic deaths and assessing risk behaviors. However, the complexity of data collection and limited coverage hinders the ability of IS to fully represent road traffic deaths in Phuket Province. Combining data sources could improve coverage and should be considered.

Combination of surveillance tools reveals that Yellow Fever virus can remain in the same Atlantic Forest area at least for three transmission seasons.

BACKGROUNDIn Brazil, the Yellow Fever virus (YFV) is endemic in the Amazon, from where it eventually expands into epidemic waves. Coastal south-eastern (SE) Brazil, which has been a YFV-free region for eight decades, has reported a severe sylvatic outbreak since 2016. The virus spread from the north toward the south of the Rio de Janeiro (RJ) state, causing 307 human cases with 105 deaths during the 2016-2017 and 2017-2018 transmission seasons. It is unclear, however, whether the YFV would persist in the coastal Atlantic Forest of RJ during subsequent transmission seasons.OBJECTIVES To conduct a real-time surveillance and assess the potential persistence of YFV in the coastal Atlantic Forest of RJ during the 2018-2019 transmission season.METHODS We combined epizootic surveillance with fast diagnostic and molecular, phylogenetic, and evolutionary analyses.FINDINGS Using this integrative strategy, we detected the first evidence of YFV re-emergence in the third transmission season (2018-2019) in a dying howler monkey from the central region of the RJ state. The YFV detected in 2019 has the molecular signature associated with the current SE YFV outbreak and exhibited a close phylogenetic relationship with the YFV lineage that circulated in the same Atlantic Forest fragment during the past seasons. This lineage circulated along the coastal side of the Serra do Mar mountain chain, and its evolution seems to be mainly driven by genetic drift. The potential bridge vector Aedes albopictus was found probing on the recently dead howler monkey in the forest edge, very close to urban areas.MAIN CONCLUSIONS Collectively, our data revealed that YFV transmission persisted at the same Atlantic Forest area for at least three consecutive transmission seasons without the need of new introductions. Our real-time surveillance strategy permitted health authorities to take preventive actions within 48 h after the detection of the sick non-human primate. The local virus persistence and the proximity of the epizootic forest to urban areas reinforces the concern with regards to the risk of re-urbanisation and seasonal re-emergence of YFV, stressing the need for continuous effective surveillance and high vaccination coverage in the SE region, particularly in RJ, an important tourist location.

A <italic>k</italic>-NN-Based Localization Approach for Crowdsourced Air Traffic Communication Networks

In this paper, we argue that current state-of-the-art methods of aircraft localization such as multilateration are insufficient, in particular for modern crowdsourced air traffic networks with random, unplanned deployment geometry. We propose an alternative, a grid-based localization approach using the k -nearest neighbor ( k -NN) algorithm, to deal with the identified shortcomings. Our proposal does not require any changes to the existing air traffic protocols and transmitters, and is easily implemented using only low-cost, commercial-off-the-shelf hardware. Using an algebraic multilateration algorithm for comparison, we evaluate our approach using real-world flight data collected with our collaborative sensor network OpenSky. We quantify its effectiveness in terms of aircraft location accuracy, surveillance coverage, and the verification of false position data. Our results show that the grid-based k -NN approach can increase the effective air traffic surveillance coverage compared to multilateration by a factor of up to 2.5. As it does not suffer from dilution of precision to the same extent, it is more robust in noisy environments and performs better in pre-existing, unplanned receiver deployments. We further find that the mean aircraft location accuracy can be increased by up to 41% in comparison with multilateration while also being able to pinpoint the origin of potential spoofing attacks conducted from the ground.

How Missing Discharge Diagnosis Data in Syndromic Surveillance Leads to Coverage Gaps

ObjectiveTo identify surveillance coverage gaps in emergency department (ED) and urgent care facility data due to missing discharge diagnoses.IntroductionIndiana utilizes the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) to collect and analyze data from participating hospital emergency departments. This real-time collection of health related data is used to identify disease clusters and unusual disease occurrences. By Administrative Code, the Indiana State Department of Health (ISDH) requires electronic submission of chief complaints from patient visits to EDs. Submission of discharge diagnosis is not required by Indiana Administrative Code, leaving coverage gaps. Our goal was to identify which areas in the state may see under reporting or incomplete surveillance due to the lack of the discharge diagnosis field.MethodsEmergency department data were collected from Indiana hospitals and urgent care clinics via ESSENCE. Discharge diagnosis was analyzed by submitting facility to determine percent completeness of visits. A descriptive analysis was conducted to identify the distribution of facilities that provide discharge diagnosis. A random sample of 20 days of data were extracted from visits that occurred between January 1, 2017 and September 6, 2017.ResultsA random sample of 179,039 (8%) ED entries from a total of 2,220,021 were analyzed from 121 reporting facilities. Of the sample entries, 102,483 (57.24%) were missing the discharge diagnosis field. Over 40 (36%) facilities were missing more than 90% of discharge diagnosis data. Facilities are more likely to be missing >90% or <19% of discharge diagnoses, rather than between those points.Comparing the percent of syndromic surveillance entries missing discharge diagnosis across facilities reveals large variability. For example, some facilities provide no discharge diagnoses while other facilities provide 100%. The number of facilities missing 100% of discharge diagnoses (n = 19) is 6.3 times that of the facilities that are missing 0% (n = 3).The largest coverage gap was identified in Public Health Preparedness District (PHPD)1 three (93.16%), with districts five (64.97%), seven (61.94%), and four (61.34%) making up the lowest reporting districts. See Table 2 and Figure 12 for percent missing by district and geographic distribution. PHPD three and five contain a large proportion (38%) of the sample population ED visits which results in a coverage gap in the most populated areas of the state.ConclusionsQuerying ESSENCE via chief complaint data is useful for real-time surveillance, but is more informative when discharge diagnoses are available. Indiana does not require facilities to report discharge diagnosis, but regulatory changes are being proposed that would require submission of discharge diagnosis data to ISDH. The addition of discharge diagnose is aimed to improve the completeness of disease clusters and unusual disease occurrence surveillance data.

Update From the Advisory Committee on Immunization Practices.

The Advisory Committee on Immunization Practices (ACIP), a group of medical and public health experts, meets 3 times per year to develop recommendations for vaccine use in the United States. The group has 15 voting members, each of whom is appointed to a 4-year term. ACIP members and Centers for Disease Control and Prevention (CDC) staff discuss the epidemiology of vaccine-preventable diseases and vaccine research, effectiveness, safety data, and clinical trial results. The ACIP met on October 25 and 26, 2017, to discuss herpes zoster vaccine, the child/adolescent and adult vaccination schedules, Japanese encephalitis (JE) epidemiology and vaccines, pneumococcal vaccines, anthrax vaccines and disaster preparedness, hepatitis A outbreaks, influenza surveillance and vaccination coverage, vaccine safety, and considerations for a potential third dose of measles-mumps-rubella (MMR) vaccine to combat ongoing mumps outbreaks. Representatives from the American Academy of Pediatrics (AAP) (Y. A. M. and D. W. K.) and the Pediatric Infectious Diseases Society (S. T. O.) were present as liaisons from their respective organizations to the ACIP.

Benefits and Challenges in Using Seroprevalence Data to Inform Models for Measles and Rubella Elimination.

Control efforts for measles and rubella are intensifying globally. It becomes increasingly important to identify and reach remaining susceptible populations as elimination is approached. Serological surveys for measles and rubella can potentially measure susceptibility directly, but their use remains rare. In this study, using simulations, we outline key subtleties in interpretation associated with the dynamic context of age-specific immunity, highlighting how the patterns of immunity predicted from disease surveillance and vaccination coverage data may be misleading. High-quality representative serosurveys could provide a more accurate assessment of immunity if challenges of conducting, analyzing, and interpreting them are overcome. We frame the core disease control and elimination questions that could be addressed by improved serological tools, discussing challenges and suggesting approaches to increase the feasibility and sustainability of the tool. Accounting for the dynamical context, serosurveys could play a key role in efforts to achieve and sustain elimination.

Strengthen the cancer surveillance to promote cancer prevention and control in China

Cancer is a major chronic disease threatening the people's health in China. We reviewed the latest advances on cancer surveillance, prevention and control in our country, which may provide important clues for future cancer control. We used data from the National Central Cancer Registry, to describe and analyze the latest cancer statistics in China. We summarized updated informations on cancer control policies, conducting network, as well as programs in the country. We provided important suggestions on the future strategies of cancer prevention and control. The overall cancer burden in China has been increasing during the past decades. In 2014, there were about 3 804 000 new cancer cases and 2 296 000 cancer deaths in China. The age-standardized cancer incidence and mortality rates were 190.63/100 000 and 106.98/100 000, respectively. China has formed a comprehensive network on cancer prevention and control. Nationwide population-based cancer surveillance has been built up. The population coverage of cancer surveillance has been expanded, and the data quality has been improved. As the aging population is increasing and unhealthy life styles persist in our country, there will be an unnegligible cancer burden in China. Based on the comprehensive rationale of cancer control and prevention, National Cancer Center of China will perform its duty for future precise cancer control and prevention, based on cancer surveillance statistics.

Geo-spatial reporting for monitoring of household immunization coverage through mobile phones: Findings from a feasibility study

BackgroundThe addition of Global Positioning System (GPS) to a mobile phone makes it a very powerful tool for surveillance and monitoring coverage of health programs. This technology enables transfer of data directly into computer applications and cross-references to Geographic Information Systems (GIS) maps, which enhances assessment of coverage and trends. ObjectiveUtilization of these systems in low and middle income countries is currently limited, particularly for immunization coverage assessments and polio vaccination campaigns. We piloted the use of this system and discussed its potential to improve the efficiency of field-based health providers and health managers for monitoring of the immunization program. MethodsUsing “30×7” WHO sampling technique, a survey of children less than five years of age was conducted in random clusters of Karachi, Pakistan in three high risk towns where a polio case was detected in 2011. Center point of the cluster was calculated by the application on the mobile. Data and location coordinates were collected through a mobile phone. This data was linked with an automated mHealth based monitoring system for monitoring of Supplementary Immunization Activities (SIAs) in Karachi. After each SIA, a visual report was generated according to the coordinates collected from the survey. ResultA total of 3535 participants consented to answer to a baseline survey. We found that the mobile phones incorporated with GIS maps can improve efficiency of health providers through real-time reporting and replacing paper based questionnaire for collection of data at household level. Visual maps generated from the data and geospatial analysis can also give a better assessment of the immunization coverage and polio vaccination campaigns. ConclusionThe study supports a model system in resource constrained settings that allows routine capture of individual level data through GPS enabled mobile phone providing actionable information and geospatial maps to local public health managers, policy makers and study staff monitoring immunization coverage.

Responding to a cVDPV1 outbreak in Ukraine: Implications, challenges and opportunities.

The European Region, certified polio-free in 2002, remains at risk of wild poliovirus reintroduction and emergence of circulating vaccine-derived polioviruses (cVDPV) until global polio eradication is achieved, as demonstrated by the cVDPV1 outbreak in Ukraine in 2015. We reviewed epidemiologic, clinical and virology data on cVDPV cases, surveillance and immunization coverage data, and reports of outbreak-related surveys, country missions, and expert group meetings. In Ukraine, 3-dose polio vaccine coverage declined from 91% in 2008 to 15% by mid-2015. In summer, 2015, two unrelated children from Zakarpattya province were paralyzed by a highly divergent cVDPV1. The isolates were 20 and 26 nucleotide divergent from prototype Sabin strain (with 18 identical mutations) consistent with their common origin and ∼2-year evolution. Outbreak response recommendations developed with international partner support included conducting three nationwide supplementary immunization activities (SIAs) with tOPV, strengthening surveillance and implementing communication interventions. SIAs were conducted during October 2015-February 2016 (officially reported coverage, round 1-64.4%, round 2-71.7%, and round 3-80.7%). Substantial challenges to outbreak response included lack of high-level support, resistance to OPV use, low perceived risk of polio, widespread vaccine hesitancy, anti-vaccine media environment, economic crisis and military conflict. Communication activities improved caregiver awareness of polio and confidence in vaccination. Surveillance was enhanced but did not consistently meet applicable performance standards. Post-outbreak assessments concluded that cVDPV1 transmission in Ukraine has likely stopped following the response, but significant gaps in population immunity and surveillance remained. Chronic under-vaccination in Ukraine resulted in the accumulation of children susceptible to polioviruses and created favorable conditions for VDPV1 emergence and circulation, leading to the outbreak. Until programmatic gaps in immunization and surveillance are addressed, Ukraine will remain at high-risk for VDPV emergence and circulation, as well as at risk for other vaccine-preventable diseases.

A mathematical analysis for controlling the spread of Nipah virus infection

Nipah virus (NiV) infection is actually a panicky fright in the South-East Asian regions. Though this emerging infectious disease is one of the most alarming threats of the public health in these regions, the treatment of this disease is limited. In this study, we propound and analyze a mathematical model for controlling the spread of NiV infection with vital dynamics (birth and death rates are not equal), incorporating the quarantines of infectious individuals influenced by availability of isolation centers and surveillance coverage. What is more, we take into account on improved personal hygiene of the susceptible population influenced by public enlightenment campaign. It has been showed with the numerical simulations that improved personal hygiene and quarantining of infectious individuals are enough to control the spread of NiV and with improved personal hygiene, it will be more effective and efficient of the two control parameters.