Regional Disease Surveillance Research Articles

Factors influencing canine rabies vaccination among dog-owning households in Nigeria

Rabies perpetuates in Nigeria despite initiatives like the Regional Disease Surveillance System Enhancement Project, with evidence indicating suboptimal canine vaccination rates as a contributing factor. To inform effective planning of mass dog vaccination campaigns, it is crucial to understand the factors associated with variation in canine vaccination rates. We conducted a cross-sectional study in 2022 to understand factors associated with canine vaccination. We used stratified random sampling of the streets and dog-owning households to survey 4162 households from three states and the Federal Capital Territory (FCT). We then built a joint probabilistic model to understand factors associated with dog vaccination and non-vaccination. First, we modelled rabies knowledge as a latent variable indirectly measured with several targeted survey questions. This method allowed a respondent's unobserved understanding of rabies to be estimated using their responses to a collection of survey questions that targeted different aspects of rabies epidemiology and took various possible response distributions (i.e., ordinal, categorical, binary). Second, we modelled factors influencing pet owners' decisions to vaccinate their dogs against rabies and barriers to dog vaccination among dog owners whose dogs were not vaccinated against rabies. Posterior distributions revealed that the probability of dog vaccination was positively associated with the owner's latent knowledge of rabies, civil servant service employment, residence in the FCT, ownership of a single dog, providing care to dogs, and a preference for contemporary treatment following a dog bite. Conversely, non-vaccination was positively associated with private employment, residing in Anambra and Enugu states, owning multiple dogs, allowing dogs to search for leftovers, and a preference for traditional treatment after a dog bite. Cost was the primary barrier against vaccination for dog owners in Anambra and Enugu, while mistrust posed a major challenge for those in the FCT. Owners in areas with veterinary establishments cited cost as a barrier, while those without a veterinary establishment cited access as the primary barrier. Our study underscores the need to enhance rabies knowledge, tailor vaccination campaigns to specific demographics, address financial and access barriers, and combat hesitancy to improve rabies vaccination rates in Nigeria.

Variable performance of DNA barcoding and morpholo­gical characteristics for the identification of Arctic black-legged Aedes (Diptera: Culicidae), with a focus on the Punctor subgroup

Abstract Arctic ecosystems face increasing risks from vector-borne diseases due to climate-driven shifts in disease patterns and vector distribution. However, species identification challenges impact vector-borne disease surveillance, necessitates accurate identification. Aedes species are predominant among Arctic mosquitoes and pose health risks, with some species potentially carrying Jamestown Canyon and Snowshoe hare viruses. However, identifying Aedes species is challenging, especially under Arctic conditions and with complex adult traits. This study assessed the suitability of DNA barcoding (COI and ITS2 regions) and morphological characteristics for the identification of Arctic black-legged Aedes. It also aimed to evaluate the reliability of publicly available sequences. Our analysis focused on Aedes impiger, Aedes nigripes, and two species from the Punctor subgroup – Aedes hexodontus and Aedes punctor. In our study, the COI barcoding region distinguished Ae. impiger and Ae. nigripes but not within the species of the Punctor subgroup. In addition, the ITS2 barcoding region did not differentiate the species. When we evaluated GenBank and BOLD sequences, we found issues of under-representation and misidentifications, particularly within the Punctor subgroup. Based on these results, we recommend addressing identification difficulties, particularly within the Punctor subgroup, and advocate for more comprehensive morphological and molecular identification strategies. Integrating morphology and DNA barcoding holds promise for robust disease surveillance in Arctic regions, yet challenges persist, especially in complex species groups like the Punctor subgroup. Tackling these issues is pivotal to ensuring accurate vector status determination and reliable disease risk assessments in a rapidly changing Arctic ecosystem.

Re-emergence of Lassa fever in Nigeria: A new challenge for public health authorities.

The Lassa virus is an RNA virus belonging to the Arenaviridae family. It is responsible for Lassa fever, an acute viral zoonosis of the severe hemorrhagic fever type with manifestations of fever, muscle pain, sore throat, nausea, vomiting, and chest and abdominal pain. Lassa fever is endemic in West Africa, where the first case was reported in 1969 in Lassa, a town in Nigeria, more than 50 years ago, and it is estimated that nearly 5000 deaths occur in West Africa each year. Nigeria is one of the endemic hotspots and has experienced numerous recurrent outbreaks of Lassa fever due to the increased multiplication of the host reservoir, Mastomys natalensis. For the Lassa epidemics in 2022 and January 2023 alone, Nigeria accounts for a quarter of the annual deaths from this disease. Poor lifestyle and hygiene, difficulty in diagnosis due to nonspecific symptomatology, lack of effective treatment based on clinical evidence, an ineffective human immunization program combined with a health system that is not adapted or equipped to control and prevent recurrent deadly epidemics, and an outdated regional disease surveillance system in West Africa are some of the challenges that must be overcome to rapidly and effectively eradicate this disease, whose area of spread is constantly expanding as a result of the movement of populations in the context of economic and socio-cultural activities.

Metagenomic surveillance uncovers diverse and novel viral taxa in febrile patients from Nigeria

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy.

Advocating for Coccidioidomycosis to Be a Reportable Disease Nationwide in the United States and Encouraging Disease Surveillance across North and South America.

Coccidioidomycosis (Valley fever) has been a known health threat in the United States (US) since the 1930s, though not all states are currently required to report disease cases. Texas, one of the non-reporting states, is an example of where both historical and contemporary scientific evidence define the region as endemic, but we don't know disease incidence in the state. Mandating coccidioidomycosis as a reportable disease across more US states would increase disease awareness, improve clinical outcomes, and help antifungal drug and vaccine development. It would also increase our understanding of where the disease is endemic and the relationships between environmental conditions and disease cases. This is true for other nations in North and South America that are also likely endemic for coccidioidomycosis, especially Mexico. This commentary advocates for US state and territory epidemiologists to define coccidioidomycosis as a reportable disease and encourages disease surveillance in other endemic regions across North and South America in order to protect human health and reduce disease burden.

Exploring Environmental and Geographical Factors Influencing the Spread of Infectious Diseases with Interactive Maps

Environmental problems due to human activities such as deforestation, urbanisation, and large scale intensive farming are some of the major factors behind the rapid spread of many infectious diseases. This in turn poses significant challenges not only in as regards providing adequate healthcare, but also in supporting healthcare workers, medical researchers, policy makers, and others involved in managing infectious diseases. These challenges include surveillance, tracking of infections, communication of public health knowledge and promotion of behavioural change. Behind these challenges lies a complex set of factors which include not only biomedical and population health determinants but also environmental, climatic, geographic, and socioeconomic variables. While there is broad agreement that these factors are best understood when considered in conjunction, aggregating and presenting diverse information sources requires effective information systems, software tools, and data visualisation. In this article, we argue that interactive maps, which couple geographical information systems and advanced information visualisation techniques, provide a suitable unifying framework for coordinating these tasks. Therefore, we examine how interactive maps can support spatial epidemiological visualisation and modelling involving distributed and dynamic data sources and incorporating temporal aspects of disease spread. Combining spatial and temporal aspects can be crucial in such applications. We discuss these issues in the context of support for disease surveillance in remote regions, utilising tools that facilitate distributed data collection and enable multidisciplinary collaboration, while also providing support for simulation and data analysis. We show that interactive maps deployed on a combination of mobile devices and large screens can provide effective means for collection, sharing, and analysis of health data.

NOMAD: metagenomic characterisation of the viral pathogen composition in outbreaks of non-malaria acute febrile illness cases

The clinical importance of non-malaria febrile acute illness (NM-AFI) in patients with a negative parasitological test has become apparent, with the progressive reduction in malaria transmission in endemic regions. Bacterial pathogens, for example Streptococcus pneumoniae and Haemophilus influenzae, which contribute disproportionally to febrile illness, are now preventable by vaccines. However, there are no vaccines, and little is known about viral NM-AFI prevalence, proliferation, virulence, and transmission chains between hosts. Although the predominant viral causes of NM-AFI are established, it is unclear if there are other NM-AFI associated emerging infectious viral pathogens that previously remained undetectable by conventional diagnostic strategies, for example severe acute respiratory syndrome coronavirus 2 (SARS-CoV-​2). Presumptive broad-spectrum antibiotic prescriptions to aparasitaemic patients not only drive drug resistance, but also lead to poor treatment outcomes. We hypothesized that insights on NM-AFI etiology, and consequently case management, could be improved by exploiting viral sequence diversity to identify viral pathogens present within metagenomics samples. We exploited simulated and existing infectious disease (Ebola, hepatitis C, chikungunya, and mosquito-borne arboviruses) metagenomic datasets to determine the composition of viral pathogens present, by implementing profile Hidden Markov Models derived from Swiss-Prot viral reference sequences for accurate pathogen detection and classification. Our analysis identified a combination of sequences from multiple viral etiological agents within the same disease sample. This approach provides a granular perspective of multiple viral etiological agents present within a single intra-host disease episode. It highlights prevalent viral strains that can subsequently be routinely detected using directed diagnostic tests to improve disease surveillance in endemic regions.

SARS-CoV-2 outbreaks on Danish mink farms and mitigating public health interventions.

BackgroundFirst severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections on Danish mink farms were reported in June 2020 and thereupon spread geographically. We provide population-level evidence on excess human incidence rates in Danish municipalities affected by disease outbreaks on mink farms and evaluate the effectiveness of two non-pharmaceutical interventions, i.e. culling of infected mink and local lockdowns.MethodsWe use information on SARS-CoV-2 outbreaks on mink farms in 94 Danish municipalities together with data on human SARS-CoV-2 cases and tested persons in Weeks 24–51 of 2020. Difference-in-difference estimation and panel event studies for weekly human incidence rates are applied to (i) identify epidemiological trends of human SARS-CoV-2 infections associated with disease outbreaks on mink farms, and (ii) quantify the mitigating effects from the two non-pharmaceutical interventions.ResultsSARS-CoV-2 outbreaks on mink farms in a municipality associate with an increase in weekly human incidence rates by about 75%; spatial spillover effects to neighbouring municipalities are also observed. Local lockdowns reduce human incidence rates, while culling of mink appears to be more effective in combination with a lockdown. The temporal lag between an outbreak on a mink farm and a significant increase in human incidence rates is estimated to be 1–3 weeks; lockdowns and culling of mink neutralize this effect 4–8 weeks after the initial outbreak.ConclusionsSARS-CoV-2 infections among farmed mink in Denmark significantly link to local human infection trends. Strict animal and human disease surveillance in regions with mink farming should be pursued internationally to mitigate future epidemic developments.

Moore swab performs equal to composite and outperforms grab sampling for SARS-CoV-2 monitoring in wastewater

Wastewater-based epidemiology (WBE) approaches to detect SARS-CoV-2 in municipal wastewater can provide unique information on the incidence or prevalence of COVID-19 in community. However, there are several technical challenges coupled with sewage sampling for SARS-CoV-2, including intermittent shedding of viruses, sampling time, volume, and frequency. Sampling schemes thus may need to be tailored to reach out highly sensitive, accurate, and reliable results. Herein, we compared the accuracy and threshold cycle (Ct) profiles of SARS-CoV-2 in Moore swabs, composite (16-h), and grab samples taken from sewage manholes (n = 17) at the Middle Eastern city of Tehran, Iran, on two occasions (November 2020 and May 2021). Samples were concentrated by polyethylene glycol precipitation and the corresponding Ct values for CDC ‘N’ and ‘ORF1ab’ assays were derived by means of real time RT-qPCR. Overall, the Moore swabs performed equal to samples composited over 16 h for qualitative monitoring, and 34/34 (100%) were positive for SARS-CoV-2. The ‘N’ assay showed the highest detection frequency as compared to ‘ORF1ab’. The mean Moore swab Ct profiles were more consistent with 16 h composite sampling as compared with corresponding grab samples, providing hints as to the best sampling protocol to adopt when planning a sewage monitoring campaign particularly under WBE. Furthermore, our analyses on local differences showed somewhat higher virus copy numbers in the southern areas. The experimental design of this study revealed that the Moore swab and composite samples are more sensitive than grab samples, suggesting that the collection of grab samples may be inappropriate for characterizing total number of viral RNA copies in sewage samples. Given the transiently presence of human host-restricted infections such as SARS-CoV-2 and the simplicity and affordability of Moore swab, the method is well suited for disease surveillance in resource poor regions struggling with limited capacity for clinical testing.

COVID-19: Learning from Past Funding Initiatives and their Dismissal in Southeast Asia

This article examines philanthropic funding of past efforts to control emerging infectious diseases in Southeast Asia and China. The recount, based on personal insights as a foundation professional and a review of both published and unpublished material, shows that American foundations and other like-minded donors identified the risks associated with zoonotic infections early on – including from the same coronavirus family that is causing the current COVID-19 pandemic – and were later followed by bilateral and multilateral donors investing greater resources. At the cusp of the 2000s, foundations played a leadership and catalyst role in advancing a transdisciplinary agenda to better understand and respond to new emerging threats and in building the necessary individual and institutional capacities for regional and local disease surveillance. For more than a decade, this concentration of resources and approaches was recognised as having contributed to better preparedness. Gradually, however, funding initiatives declined in value and intensity due to several internal and external factors. This article argues that COVID-19 arrives in the midst of an unfinished donor agenda and that it is important to reflect on why philanthropic foundations, and the development aid community more generally, found themselves unprepared for the pandemic in order to draw lessons for addressing today’s crisis – and future outbreaks of emerging infectious diseases.

Beyond SARS-CoV-2: Lessons That African Governments Can Apply in Preparation for Possible Future Epidemics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed unprecedented pressure on healthcare systems, even in advanced economies. While the number of cases of SARS-CoV-2 in Africa compared to other continents has so far been low, there are concerns about under-reporting, inadequate diagnostic tools, and insufficient treatment facilities. Moreover, proactiveness on the part of African governments has been under scrutiny. For instance, issues have emerged regarding the responsiveness of African countries in closing international borders to limit trans-continental transmission of the virus. Overdependence on imported products and outsourced services could have contributed to African governments’ hesitation to shut down international air and seaports. In this era of emerging and re-emerging pathogens, we recommend that African nations should consider self-sufficiency in the health sector as an urgent priority, as this will not be the last outbreak to occur. In addition to the Regional Disease Surveillance Systems Enhancement fund (US$600 million) provided by the World Bank for strengthening health systems and disease surveillance, each country should further establish an epidemic emergency fund for epidemic preparedness and response. We also recommend that epidemic surveillance units should create a secure database of previous and ongoing pandemics in terms of aetiology, spread, and treatment, as well as financial management records. Strategic collection and analysis of data should also be a central focus of these units to facilitate studies of disease trends and to estimate the scale of requirements in preparation and response to any future pandemic or epidemic.

Evaluating Chronic Disease Surveillance Systems: Lessons Learned From Applying a Framework to Assess the Alaska Behavioral Risk Factor Surveillance System

Chronic diseases with behavioral risk factors are now the leading causes of death in the United States. A national Behavioral Risk Factor Surveillance System (BRFSS) monitors those risk factors; however, there is a need for national and state evaluations of chronic disease surveillance systems. The Department of Health and Human Services/Centers for Disease Control and Prevention (CDC) has developed a framework on evaluating noncommunicable disease–related surveillance systems; however, no implementation of this framework has yet been published. This article describes the process of, and offers lessons learned from, implementing the evaluation framework to assess the Alaska BRFSS. This implementation evaluation may inform assessments of other state and regional chronic disease surveillance systems and offers insight on the positive potential to consult key stakeholders to guide evaluation priorities.

Learning Transferable Driven and Drone Assisted Sustainable and Robust Regional Disease Surveillance for Smart Healthcare.

Smart healthcare has been applied in many fields such as disease surveillance and telemedicine, etc. However, there are some challenges for device deployment, data collection and guarantee of stainability in regional disease surveillance. First, it is difficult to deploy sensors and adjust the sensor network in unknown region for dynamic disease surveillance. Second, the limited life-cycle of sensor network may cause the loss of surveillance data. Thus, it is important to provide a sustainable and robust regional disease surveillance system. Given a set of Disease surveillance Area (DsA)s and Point of disease Surveillance (PoS)s, some sensors are deployed to monitor these PoSs, and a drone collect data from the sensors as well as charge the sensors to extend their life-cycles. The drone replenish its energy by relying on the bus network. We first formulate the drone assisted regional disease surveillance problem under the constraints of life-cycle of sensors and energy of drone, and propose an approximation algorithm to find a feasible cycle of drone to minimize the traveling time cost of drone. To satisfy the diversity requirements and dynamic scalability of regional disease surveillance, we deploy one robot in each DsA instead of sensors. We further formulate the learning transferable driven regional disease surveillance problem, and propose a joint schedule algorithm of drone and robots. The results of both theoretical analysis and extensive simulations show that the proposed algorithms can reduce the total time cost by 39.71 and 48.74 percent, average waiting time by 42.00 and 50.14 percent, and increase the average accessing ratio of PoSs by 15.53 and 22.30 percent, through the assistance of bus network and learning transferable features.

Enabling semantic interoperability of regional trendsof disease surveillance data for Namibia througha health-standards-based approach

The Ministry of Health and Social Services in Namibia under the division of epidemiology uses a manual paper-based approach to capture disease surveillance data through 5 levels of reporting, the levels being communitylevel, health facility level, district level, regional level, and national level. As a result, this method of communicatingand exchanging disease surveillance information is cost and time consuming, which prevents disease surveillanceinformation from reaching the head office on time. The current method used to exchange and communicate diseasesurveillance data is a manual process and very time consuming due to the fact that surveillance officers have toorganize and store the files and hunt down the information when it is needed. Therefore, the study developed aprototype that aggregates disease surveillance data from 14 regions in Namibia and can thus enable the diseaseservice office to capture disease surveillance data through the use of mobile devices. The functionality of theprototype would allow a disease surveillance officer in one regional office to access the data of other regionaloffice in real time. The method used to communicate disease surveillance data is through the excel spreadsheet(IDSR), which is called the integrated disease surveillance and response. Furthermore, the excel file will be sentto the relevant authority through email. However, we still do not have a web-based system to report cases ofdiseases. Instead, this is a process starting from the intermediate hospital disease surveillance data, which iscaptured then sent to the regional office and from the regional office to the district office and then to the nationaloffice and from the national office the information is further sent to the WHO and other development partners aswell as to the top management or to the highest authority. So it does not end at the national level but goes tomanagement such as the Permanent Secretary, and the data is used to inform the development partners, and thenational surveillance office prepares official letters to the management as a form of reporting disease surveillancedata. The symphonic surveillance office helps to detect a particular disease. The doctors send an investigationcase form to the laboratory for testing the disease that has been identified.

Establishing National Multisectoral Coordination and collaboration mechanisms to prevent, detect, and respond to public health threats in Guinea, Liberia, and Sierra Leone 2016\u20132018

BackgroundThe governments of Guinea, Liberia, and Sierra Leone have acknowledged that weak health systems and poor coordination of efforts hampered effectiveness of the 2014–2016 Ebola outbreak response. The bitter experience of the Ebola outbreak response served as an important catalyst for increased efforts to comply with World Health Organization (WHO) International Health Regulations (IHR 2005), Performance of Veterinary Services (PVS) Pathway capacities, and Global Health Security Agenda (GHSA) goals. In November 2016, an interministerial meeting held in Dakar, Senegal, resulted in formalized commitments from the three nations to strengthen resilience to health threats by establishing a Regional Strategic Roadmap to institutionalize the One Health approach. Since then, each country has made significant progress towards establishing National One Health Platforms to coordinate health security interventions, in collaboration with international partners. This paper outlines the methodology and results of these efforts for the period June 2016–January 2019, with a specific focus on activities supported by the US Agency for International Development (USAID)-funded Preparedness & Response (P&R) project.ObjectivesIn support of the West African Health Organization’s November 2016 Regional Strategic Roadmap for institutionalization of the One Health approach, the Preparedness & Response (P&R) project worked in coordination with national partners in Guinea, Liberia, and Sierra Leone to establish multisectoral, One Health coordinating mechanisms.MethodologyThe global USAID-funded P&R project was launched in 2014 to support the achievement of this objective, and began coordinating with partners in Guinea, Liberia, and Sierra Leone in 2016 to tailor its multi-step conceptual framework to fit the priorities and operating constraints of national stakeholders. Organized in phases of Collaboration (building key relationships), Formalization (defining and establishing a coordination structure), and Implementation (using newfound coordination to produce better health security outcomes), the framework features steps such as One Health sensitizations for multisectoral national stakeholders, development of One Health platform terms of reference and other operating guidelines, and application of these tools to coordination of technical assistance during outbreaks.ResultsIn Guinea, Liberia, and Sierra Leone, in less than 3 yrs there has been a marked improvement in cross-sectoral coordination on health security actions. All three countries have passed legislation establishing permanent multisectoral coordination mechanisms referred to in this document as National One Health Platforms, or simply Platforms; instituted an annual mechanism for assessing capacity and performance of these platforms to lead health security actions; and have undertaken key steps towards developing and updating National Preparedness & Response Plans which truly reflect the multisectoral nature of emerging disease threats. However, multisectoral coordination is a work in progress: government stakeholders and their international partners continue to work together to further strengthen national ownership and investment in the newly established Platforms.Conclusion and next stepsNewly established Platforms in Guinea, Liberia, and Sierra Leone offer a long-term structure for coordinating health security actions. However, given the short period of time since their formalization, they depend on continued national, regional, and international resources to build from recent progress and further improve capacity and performance. Regional programs such as the World Bank Regional Disease Surveillance Systems Enhancement (REDISSE) project are of critical importance in keeping the momentum going. The highlighted progress and outputs to date provide reasons and motivation for continued, longer-term investment in the Platforms.

Of sheep, sentinels and surveillance: what is the new ‘normal’?

#### What you need to know In the UK and Ireland, networks of veterinary investigation centres – also known as regional veterinary laboratories and disease surveillance centres – serve their...

Learning the seasonality of disease incidences from empirical data

Investigating the seasonality of disease incidences is very important in disease surveillance in regions with periodical climatic patterns. In lieu of the paradigm about disease incidences varying seasonally in line with meteorology, this work seeks to determine how well simple epidemic models can capture such seasonality for better forecasts and optimal futuristic interventions. Once incidence data are assimilated by a periodic model, asymptotic analysis in relation to the long-term behavior of the disease occurrences can be performed using the classical Floquet theory, which explains the stability of the existing periodic solutions. For an illustrative case, we employed infected-recovered models with an infection rate of a single period and that of commensurate periods to assimilate weekly dengue incidence data from the city of Jakarta, Indonesia, which we present in their raw and moving-average-filtered version. To estimate the infection rate of a single period, eight optimization schemes were assigned returning magnitudes of the rate that vary insignificantly across schemes. Three schemes were assigned to estimate the infection rate of commensurate periods based on three different sets of periods used. Each scheme involving commensurate periods gives better fitting than that involving only a single period. The computation results combined with the analytical results indicate that if the disease surveillance in the city does not improve, then the incidence will raise to a certain positive orbit and remain cyclical.

ANTIMICROBIAL RESISTANCE: UNIVERSAL EMERGENCY

Antimicrobial resistance (AMR) is a growing public health threat. Resistant microorganisms (i.e. bacteria, viruses and some parasites) through genetic mutations become too strong that they become resistant to the antimicrobials (i.e. antibiotics, antivirals and antimalarial) over the period.1 These microorganisms are present in our environment, spreading from one person to another and from animals to human beings.2 While a considerable burden of AMR is suspected, it is difficult to quantify mortality, disease load and economic loss related to AMR due to the absence of data in Southeast Asia.3 AMR causes prolonged illness, surplus tests, consumption of expensive drugs, intensive care, compromised surgeries, chemotherapy, disability and death. AMR can jeopardize the achievements of the Sustainable Development Goals (SDGs). Resistance is emerging and spreading globally. Many patients with Klebsiella pneumoniae had developed resistance against Carbapenem (last choice for the treatment of gram-negative bacteria) in all regions of the world. Patients with urinary tract infections caused by Escherichia coli are now resistant to fluoroquinolone. In at least 10 developed countries of the world, third generation Cephalosporins are ineffective against the treatment of gonorrhea. World Health Organization (WHO) does not recommend quinolones for the treatment of gonorrhea anymore and has updated treatment guidelines for chlamydial and syphilis infections. Staphylococcus aureus patients are resistant to first-line drug i.e. methicillin. Resistance to colistin, the last remedy for Enterobacteriaceae, has been detected. Alarmingly, extensively drug-resistant tuberculosis (XDR-TB) and multidrug-resistant tuberculosis (MDR-TB) are types of tuberculosis resistant to no less than four and two of the key anti-tuberculous drugs respectively have emerged. XDR-TB has been identified in 105 countries.4 About 480,000 new cases of MDR-TB have been estimated by WHO during 2014. In 2016, around 490,000 people developed MDR-TB worldwide. Five countries of the Greater Mekong are now resistant to the artemisinin-based combination therapies considered as first-line treatment for Plasmodium falciparum malaria since 2016. All Anti-Malarial treatment options for Plasmodium falciparum are now ineffective along the Cambodia-Thailand border. About 7% of patients in developing countries and 10-20% of patients from developed countries were estimated to have human immunodeficiency virus (HIV) resistant to antiretroviral therapy (ART) in 2010. Antiviral drugs i.e. matrix-2 (M2) inhibitors (Amantadine & Rimantadine) are now ineffective to treat the Influenza A virus. Outbreaks of multidrug resistance Typhoid and sporadic cases of infection with Ceftriaxone-resistant Salmonella typhi have been reported in several countries of the world. Recently Pakistan's first extensively drug-resistant (XDR) Salmonella typhi outbreak (resistant to all antibiotics for Typhoid) has created an emergency in the country. The ongoing outbreak had emerged in the district Hyderabad of Pakistan.5 In May 2018, the official case definitions were agreed by the Regional Disease Surveillance and Response Unit (RDSRU) in Karachi. Out of the 8,188 Typhoid cases, 5,274 cases of XDR were reported till December 2018. Among them 69% of the cases were reported from Karachi, 27% from Hyderabad and 4% from other districts of the Sindh province. Currently, Salmonella typhi in circulation is resistant to first, second as well as third generation Cephalosporins. Currently, azithromycin is the only remaining reliable and cost-effective first-line oral therapy to manage patients with XDR Typhoid in low-resource settings.The risk of XDR Salmonella typhi at the national level is considered high in Pakistan due to insufficient unsafe water supply systems, poor sanitation and hygiene (WASH) practices, poor infection control mechanisms, inappropriate food-handling, low vaccination coverage and limited surveillance of Typhoid fever. At the same time antibiotics are not being prescribed properly to the humans as well as animal sector. Furthermore, AMR confirmatory tests are available only at major laboratories and tertiary care hospitals. All these factors have reduced the ability to track the occurrence, spread and containment of XDR Salmonella typhi in Pakistan. Access to safe water, adequate sanitation, hospital sanitation and cleanliness, hygiene among food handlers, advocacy, social mobilization, sensitization of general practitioners/clinicians, Typhoid conjugate vaccination and development of new antibiotics are the most important recommendations for prevention of the AMR concerning XDR Salmonella Typhi in Pakistan.6-7 Besides, strengthening the surveillance to monitor known resistance, detect new and emerging trends is the need of the hour.

Characterizing Tweet Volume and Content About Common Health Conditions Across Pennsylvania: Retrospective Analysis.

BackgroundTweets can provide broad, real-time perspectives about health and medical diagnoses that can inform disease surveillance in geographic regions. Less is known, however, about how much individuals post about common health conditions or what they post about.ObjectiveWe sought to collect and analyze tweets from 1 state about high prevalence health conditions and characterize the tweet volume and content.MethodsWe collected 408,296,620 tweets originating in Pennsylvania from 2012-2015 and compared the prevalence of 14 common diseases to the frequency of disease mentions on Twitter. We identified and corrected bias induced due to variance in disease term specificity and used the machine learning approach of differential language analysis to determine the content (words and themes) most highly correlated with each disease.ResultsCommon disease terms were included in 226,802 tweets (174,381 tweets after disease term correction). Posts about breast cancer (39,156/174,381 messages, 22.45%; 306,127/12,702,379 prevalence, 2.41%) and diabetes (40,217/174,381 messages, 23.06%; 2,189,890/12,702,379 prevalence, 17.24%) were overrepresented on Twitter relative to disease prevalence, whereas hypertension (17,245/174,381 messages, 9.89%; 4,614,776/12,702,379 prevalence, 36.33%), chronic obstructive pulmonary disease (1648/174,381 messages, 0.95%; 1,083,627/12,702,379 prevalence, 8.53%), and heart disease (13,669/174,381 messages, 7.84%; 2,461,721/12,702,379 prevalence, 19.38%) were underrepresented. The content of messages also varied by disease. Personal experience messages accounted for 12.88% (578/4487) of prostate cancer tweets and 24.17% (4046/16,742) of asthma tweets. Awareness-themed tweets were more often about breast cancer (9139/39,156 messages, 23.34%) than asthma (1040/16,742 messages, 6.21%). Tweets about risk factors were more often about heart disease (1375/13,669 messages, 10.06%) than lymphoma (105/4927 messages, 2.13%).ConclusionsTwitter provides a window into the Web-based visibility of diseases and how the volume of Web-based content about diseases varies by condition. Further, the potential value in tweets is in the rich content they provide about individuals’ perspectives about diseases (eg, personal experiences, awareness, and risk factors) that are not otherwise easily captured through traditional surveys or administrative data.

The role of connected diagnostics in strengthening regional, national and continental African disease surveillance.

No abstract available.