Data on type-specific human papillomavirus (HPV) are needed to investigate HPV-based screening tests and HPV vaccines. However, Chinese relevant data are insufficient. Therefore, this meta-analysis aimed to summarize and demonstrate the prevalence and distribution of HPV genotypes in cervical intraepithelial neoplasia (CIN) and compensate for the shortage of HPV vaccines in China.The Medline, Embase, and the Cochrane Library databases, as well as references cited in the selected studies, were systematically searched for studies investigating the prevalence and distribution of HPV genotypes between January 2000 and April 2019 in China.χ2 = 80.095, P < 0.001). The most common HPV types in CIN1 in order of decreasing prevalence were as follows: HPV52 (20.31%), HPV16 (16.81%), HPV58 (14.44%), HPV18 (6.44%), and HPV53 (5.76%). However, in the CIN2/3 group, HPV16 (45.69%) was the predominant type, followed by HPV58 (15.50%), HPV52 (11.74%), HPV33 (9.35%), and HPV31 (4.34%).A total of 8 studies were identified, which comprised 2950 patients with CIN1 and 5393 with CIN2/3. The overall HPV infection rate was 84.37%. The HPV infection rate was significantly higher in the CIN2/3 group (87.00%) than in the CIN1 group (79.56%) (This study suggested that HPV16, HPV52, and HPV58 were the top three types of CIN in China. The findings might provide a reference for future HPV-based cervical cancer screening tests, treatment of HPV infection, and application of HPV vaccines in China. Of the 570,000 new patients of cervical cancer reported worldwide in 2018, more than 310,000 patients died . Thus, cThe genome of HPV comprises a double-strand circular DNA of 8000 base pairs. More than 100 types of HPVs have been identified so far. They are divided into two categories: HR-HPV and low-risk HPV (LR-HPV). Furthermore, 80% of women are infected with HPV in their lifetime; however, around 90% of infections disappear . It is gAt present, the use of HPV vaccines is one of the most important ways to refrain from HPV infection . HoweverThe Medline, Embase, and the Cochrane Library databases, as well as references cited in the selected studies, were systematically searched for studies investigating the prevalence and distribution of HPV genotypes between January 2000 and April 2019 in China. The key search items included “cervical intraepithelial neoplasia,” “human papillomavirus,” “polymerase chain reaction,” “epidemiology,” “genotype,” “China,” “female,” and so forth. The meta-analysis was restricted to studies published between January 2000 and April 2019. The analysis had no language restrictions.The inclusion criteria were as follows: (1) research related to opportunistic screening in hospitals, (2) CIN1, CIN2, and CIN3 diagnosed by cervical histopathology, (3) each targeted study contained a minimum of 20 CIN cases, (4) HPV-DNA detected by polymerase chain reaction (PCR), and (5) at least 10 identified HPV types. The exclusion criteria were as follows: (1) no pathological result found, (2) the grouping included cervical cancer, and (3) the requisite information could not be accessed.The data from all the studies were collected and checked simultaneously by the researchers. The main extracted information included the first author name, reference, research location, HPV-DNA source, PCR primers, sample capacity, and HPV prevalence  of more than 95% were used for the correlation analysis. The statistical analysis used the CI and heterogeneity test combined with the rate of logit transformation. Review Manager 5.3 was used for the meta-analysis of the correlation between HPV infection and cervical lesions. When A total of 79 potentially related studies were identified by screening Medline, Embase, and the Cochrane Library. Of these, 10 studies presented duplicate reports and 40 had nothing to do with the epidemiological characteristics of HPV. Ultimately, nine studies were included in the meta-analysis after full-text screening . The litI2 = 97%, P < 0.00001). Unfortunately, an obvious bias was found. Subsequently, the infection rate of the most representative HPV16 was explored in the meta-analysis of CIN2/3 and CIN1 groups. As a result, a moderate heterogeneity  was noted, and the bias decreased significantly.A meta-analysis of total HPV infection rates was carried out in the CIN2/3 and CIN1 groups. The random-effects model was used because of significant heterogeneity  or apparent bias was found . In the CIN1 group, HPV52 (20.31%), HPV16 (16.81%), HPV58 (14.44%), HPV18 (6.44%), and HPV53 (5.76%) were the most common types. Yet, in the CIN2/3 group, HPV16 (45.69%), HPV58 (15.50%), HPV52 (11.74%), HPV33 (9.35%), and HPV31 (4.34%) were the most common types. The infection rate of each type was dramatically different between the two groups (Table The samples included 2950 patients with CIN1 and 5393 with CIN2/3. The HPV infection rate was significantly higher in the CIN2/3 group (87.00%) than in the CIN1 group (79.56%) . However, no obvious difference was found in the multiple HPV infection rate between the two groups  , consistHPV16 has the highest incidence of cervical cancer, while the distribution of other types varies regionally in different countries . Some meTherefore, it was concluded that the main types of HPV infection in the CIN1 and CIN2/3 groups were different. Furthermore, the infection rate of each genotype was markedly diverse for cervical lesions of different degrees. It was confirmed again that the most common HPV genotypes among Chinese women were different from those in non-Asian countries. According to the “2012 Updated Consensus Guidelines for the Management of Abnormal Cervical Cancer Screening Tests and Cancer Precursors,” HPV16- or HPV18-infected women were supposed to first undergo colposcopy despite negative results on cytologic evaluation . HoweverThe safety and efficacy of HPV vaccines have been confirmed . At presχ2 = 62.875, 22.113, P < 0.001) [The types of HPV infection are diverse depending on the difference in the susceptibility of different individuals. Several studies showed that a single HPV infection was dominant, while multiple HPV infections were prevalent in large populations , 29. Res< 0.001) . In the < 0.001) , was an < 0.001) . TherefoThe present study had several limitations. First, HPV results were influenced by the DNA source and detection techniques. Second, despite the detailed description of type-specific HPV, the analysis of multiple HPV infections was simple. The influence of co-infection with different genotypes on CIN was of great significance. Third, it was meaningful to group cases by region or ethnicity. Last but not least, the study was limited to the investigation of CIN and lacked data on healthy people and patients with cervical cancer. Therefore, more detailed investigations are needed in the future.In conclusion, the distribution of papillomavirus genotypes in China basically resembles that in other parts of the world. HPV16, HPV52, and HPV58 are the most common types of CIN in China. At present, the universal HPV Gardasil 9 vaccine is effective against most of the HPV types worldwide. However, the existing HPV vaccines do not play any role against HPV53, which has a high prevalence rate. This study provided a reference for future HPV-based cervical cancer screening tests, treatment of HPV infection, and application of HPV vaccines in China.


High risk-human papillomaviruses (HPVs) are known carcinogens. Numerous reports have linked the steroid hormone estrogen, and the expression of estrogen receptors (ERs), to HPV-related cancers, although the exact nature of the interactions remains to be fully elucidated. Here we will focus on estrogen signaling and describe both pro and potentially anti-cancer effects of this hormone in HPV-positive cancers. This review will summarize: (1) cell culture-related evidence, (2) animal model evidence, and (3) clinical evidence demonstrating an interaction between estrogen and HPV-positive cancers. This comprehensive review provides insights into the potential relationship between estrogen and HPV. We suggest that estrogen may provide a potential therapeutic for HPV-related cancers, however additional studies are necessary. Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States. Furthermore, the virus accounts for approximately 5% of all worldwide cancers ,5,6,7,8.Human papillomaviruses (HPVs) are small, double stranded DNA viruses. While there are numerous types of HPV, this review will focus on alpha-papillomaviruses with the propensity to infect mucosal epithelial cells, and are further characterized as high-risk by their predisposition to immortalize human keratinocytes and cause pre- and malignant lesions. Among these high-risk alpha-papillomaviruses are HPV 16, 18, 31, 33, 45, 52, and 58. These viral strains are estimated to contribute to at least 90% of all HPV-related cancers and are all included in the newest vaccine, Gardasil 9 ,12,13. Wcis elements that are necessary for the control of viral replication and transcription [All HPVs share common genetic structures that consist of approximately 8000 base pairs, encoding around eight open-reading frames (ORFs) ,15,16. Tcription ,18,19. Tcription . The latcription ,15,21. Lcription ,23.The brunt of human cellular changes induced by the virus occur through interactions with the early proteins. HPV E2 is a DNA-binding protein that acts to recognize the viral origin of replication contained within the LCR. When E2 binds the origin, it recruits E1, the viral helicase and the only enzyme encoded for in the viral genome. E1 and E2 work together to recruit various cellular factors including host polymerases to allow for the replication of the viral genome ,34,35,36The HPV lifecycle is inextricably linked to the differentiation of infected epithelia ,45. InitCircumventing the normal loss of cellular division over time is thought to be how HPV replication leads to tumorigenesis . Loss of17β-estradiol, the predominant form of circulating estrogen, is a steroid hormone that plays a vital role in both sexes. It is well known that estrogen is exceptionally important in the regulation of the menstrual cycle in females and is highly abundant during a female’s reproductive years . The sigEstrogen is primarily sourced in the ovaries, however, it can also be synthesized in the adrenal glands and adipose tissue of both males and females ,70,71,72ERα is encoded for by the gene ESR1, and is found on chromosome 6 ,83,84. EThere is a solid foundation of evidence suggesting that estrogen signaling is involved in carcinogenesis. Estrogen-receptor complexes can regulate cell cycle progression and cell proliferation ,115,116.The Lambert laboratory and collaborators have demonstrated that the expression of the estrogen receptor α and E7 expression are intrinsically linked to the development and persistence of HPV-related cervical dysplasia and cervical cancer ,129,130.Further evidence linking estrogen signaling to HPV-related carcinogenesis can be found in the clinic, although this data has confounding factors. The first reports linking sex hormones to genital cancers were noted in 1971. Since then, a number of additional studies have confirmed that the use of diethylstilbestrol (DES) by pregnant women, dramatically increased the risk of cervical cancer development in their daughters that were exposed in utero ,133,134.There is significant evidence suggesting that estrogen may serve as a treatment modality in HPV-related lesions and cancers. The HPV18+ cervical cancer cell line, HeLa, is particularly sensitive to estrogen treatment ,139,140.A recent report demonstrated that high ERα expression in laryngeal squamous cell carcinoma (LSCC) correlated with improved survival . While tWhile there is limited evidence in animal models, patient studies provide evidence that the expression of the ER correlates with improved clinical outcomes, and that estrogen treatment could potentially enhance these outcomes. Recently, a number of studies have analyzed the expression of ERα in the TCGA ,146,147.n = 23,000, whereas for males n = 15,800 [n = 12,600). By comparison, females only present approximately 3100 yearly cases of HPV+OPCs in this data set; suggesting a 4:1 ratio of men:women for HPV+OPC [Further estrogenic clinical evidence can be observed in sex-related differences comparing both the frequency and the severity of HPV+HNSCC. = 15,800 ,155. Bre HPV+OPC ,155. As  HPV+OPC . Among t HPV+OPC . This su HPV+OPC . While t HPV+OPC . While f HPV+OPC ,160,161.Reliable methods to test for HPV are difficult in the clinic due to low protein expression. For this reason, the surrogate marker, p16, is utilized to test for HPV infections in tissue sections. p16 shares an inverse relationship with the expression levels of pRb, which is degraded by E7 . AlthougEstrogen and related sex hormones are linked to immunity ,164. It Even with the prophylactic vaccine, HPV continues to present a worldwide disease burden. This is augmented by the lack of reliable tests for many of the areas infected by the virus, and by the lack of antiviral treatments. One possible antiviral-targeted approach could be related to estrogen signaling. There is clear evidence that estrogen-ER signaling has a multifaceted relationship with HPV-related infections and cancer. Given the conflicting evidence, it is difficult to present overall conclusions. Extrapolating from current animal studies, it is clear that ERα does play a role in the development of cervical cancer. However, while it must be present for tumors to develop, it does not necessarily mean that estrogen causes cancer. Our previous cell culture work has indicated that HPV+ epithelia also express ERα; however, this allows for HPV-specific sensitivity to estrogen, both at the level of transcription via interactions with the LCR, and at the level of E6 and E7 expression . If ther


Blue spaces have been found to have significant salutogenic effects. However, little is known about the mechanisms and pathways that link blue spaces and health. The purpose of this systematic review and meta-analysis is to summarise the evidence and quantify the effect of blue spaces on four hypothesised mediating pathways: physical activity, restoration, social interaction and environmental factors. Following the PRISMA guidelines, a literature search was conducted using six databases . Fifty studies were included in our systematic review. The overall quality of the included articles, evaluated with the Qualsyst tool, was judged to be very good, as no mediating pathway had an average article quality lower than 70%. Random-effects meta-analyses were conducted for physical activity, restoration and social interaction. Living closer to blue space was associated with statistically significantly higher physical activity levels . Shorter distance to blue space was not associated with restoration  or social interaction . Larger amounts of blue space within a geographical area were significantly associated with higher physical activity levels  and higher levels of restoration . Being in more contact with blue space was significantly associated with higher levels of restoration . There is also evidence that blue spaces improve environmental factors, but more studies are necessary for meta-analyses to be conducted. Evidence is conflicting on the mediating effects of social interaction and further research is required on this hypothesised pathway. Blue spaces may offer part of a solution to public health concerns faced by growing global urban populations. The world’s urban population has grown by approximately 460% between 1950 and 2018, increasing the number of people living in urban areas from 751 million in 1950 to 4.2 billion in 2018 , as wellNatural environments bring several benefits to public health and social wellbeing in urban settings. Studies have shown that exposure to natural environments contributes to reduced mortality rates and increased wellbeing among urban dwellers . Most ofIn order to leverage these salutogenic effects and improve the health of the urban population, it is important to understand the linking mechanisms between exposure to blue space and health. Four mechanisms have been proposed to mediate the relationship between blue spaces and health : (1) AccTo date there has been no review synthesising evidence about these potential mechanisms.The purpose of this systematic review and meta-analysis is to summarise current evidence and quantify the effect of blue space on physical activity, restoration, environmental factors and social interaction.http://www.crd.york.ac.uk/PROSPERO/ (accessed on 22 January 2021) with registration number CRD42019154917).This systematic review and meta-analysis followed the PRISMA guidelines and the composition of systematic reviews in research guidelines ,21. The Six databases ) were searched for articles using keywords and synonyms of terms pertaining to urban green and blue spaces  and potential mechanisms or mediating factors . For each database, a search string was created, combining these keywords ), sample size, design, main results, area/context, blue space exposure, method of blue space exposure measurement, and confounding variables.Quality appraisal of studies was conducted by two reviewers using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields QUALSYST tool . This to2 statistics. With upper limits of 25%, 50% and 75% respectively for I2, heterogeneity was interpreted as medium, moderate, or high [Studies were classed according to how exposure to blue space was measured  and the mechanism/mediator investigated, by two study authors . A meta-analysis was conducted when at least three studies were available for the same exposure and mechanism/mediator combined. Meta-analyses were feasible for the association between the amount of blue space and physical activity, distance to blue space and physical activity, amount of blue space and restoration, distance to blue space and restoration, contact with blue space and restoration and distance to blue space and social interaction. Other categories did not have a sufficient number of articles or did not report sufficient statistics to permit a meta-analysis. Prior to each meta-analysis, the effect size of blue space of each study was extracted and converted to Cohen’s d, based on conversion methods for effect sizes in the existing literature ,26. Effe or high . All met or high . Forest  or high .The electronic searches identified 13,206 articles; 9122 in PubMed, 47 in Scopus, 1136 in PsycInfo, 1843 in Web of Science, 53 in Cochrane Library, and 1005 in CINAHL (EBSCO). 26 more papers, meeting the inclusion criteria, were added to the database from the snowball search. After removing duplicates, 106 articles were found to be eligible for full-text screening. This resulted in 50 studies being included in the review. The main reasons for excluding studies were that studies did not measure the right exposure, were qualitative, were conducted in a virtual environment or referred solely to impacts of green space. The data flow is presented in Among the 50 articles included in this review, 35 articles had a cross-sectional design ,63,64,65The association between physical activity and exposure to blue spaces was examined in 18 papers ,72,78,79Out of the 14 papers showing an association between blue spaces and physical activity, 10 papers showed a positive impact either on walking or MVPA ,70,77,78Cycling was used as a physical activity indicator in two of the 14 papers showing an association between blue spaces and physical activity ,34.In general, all 18 physical activity related papers were of very good quality, with an average quality score of 88.12%. Papers were downgraded mainly due to insufficient justification of their methods of blue space measurement and the need for a more detailed explanation of their statistical analyses. Quality scores are provided in There was sufficient data to meta-analyse the effect of distance between blue space and dwelling/neighbourhood and the effect of the amount of blue space on physical activity.The meta-analysis between distance to blue space and physical activity included 11 studies ,57,70,77The meta-analysis between the amount of blue space and physical activity included nine studies ,77,78,792 of 99.49% and 99.34% for the association between distance to blue space and amount of blue space, respectively, with physical activity.Considerable heterogeneity was present in both models with an IThe association between exposure to blue spaces and restoration was explored in 21 articles ,72,75,79More specifically, seven studies found a beneficial effect of blue space availability or visibility on stress or psychological distress ,63,66,71Overall, the 21 restoration–related articles were judged as of very good quality with an average quality score of 88.77%. The main reasons for lower quality scores were the insufficient justification of methods of blue space measurements and the lack of a detailed description of input variables. Quality scores are provided in Sufficient data were available to conduct a meta-analysis of the association between distance to blue space and restoration, amount of blue space within a geographical area and restoration, contact with blue space and restoration.2 = 91.97%) (2 = 96.60%) (2 = 79.50%)  a. Having 96.60%) b and bei 79.50%) c. High hSocial interaction was associated with exposure to blue spaces in seven articles ,57,61,73More specifically, De Bell et al.  found thThe social interaction related articles were judged to be of very good quality with an average quality score of 88.95%. The main reason for lower quality scores was insufficient details when reporting results. Quality scores are provided in There were sufficient data to meta-analyse the effect of amount of blue space within a geographical area on social interaction and the effect of distance to blue space on social interaction.2 = 90.81%)  a.2 = 56.41%)  b.Environmental factors were found to be associated with the presence of blue spaces in 14 articles ,68,74,76Five articles found a positive effect of blue spaces on temperature ,53,64,65Overall, the 14 articles presenting an association between blue space presence and environmental factors were judged as of good quality with an average quality score of 80.43%. The main reasons for lower quality scores were insufficient details in the presentation of results, lack of confounding variables and reported statistics, complex study design and lack of a detailed justification of the methods. Quality scores are provided in This review aimed to synthesise the existing evidence about the mechanisms that mediate the impact of blue space on health, specifically physical activity, restoration, social interaction and environmental factors, and quantify these pathways. Fifty studies were included in our systematic review, of which 27 studies provided data for meta-analyses.Overall, there was evidence to indicate that blue space increases physical activity, enhances restoration and improves environmental factors. Blue space may also have a beneficial effect on social interaction, but the evidence was mixed and further research is needed on this hypothesised pathway. Thus, three of the four hypothesised pathways  are supported by empirical evidence, while findings for social interaction are inconclusive.Interestingly, the beneficial effects of blue space on physical activity were almost equally obtained through a shorter distance of someone’s residence to blue space  and a greater amount of blue space around a geographical area . Empirical evidence, therefore, suggests that the development of blue space within shorter distances to residences and increasing the amount of blue space within neighbourhoods could significantly benefit health through the mediating pathway of physical activity.Our meta-analyses indicated that the blue space benefits on restoration where mainly acquired through a higher amount of blue space within a geographical area , compared to increased contact with blue space . Intriguingly, the increase of amount of blue space within a geographical area was found to be the highest among all mediating pathways and exposures. This evidence, therefore, suggests that developing more blue spaces within neighbourhoods could primarily benefit the restorative character of an area. Living closer to blue space was not found to significantly affect restoration . While urbanicity has been found to increase mental disorders through social stress , we propOur systematic review suggests that several environmental phenomena, such as heat stress and low air quality can benefit from the development of blue space in urban settings. The evidence base was small, heterogeneous in terms of environmental definitions and measures  and mainly focused on heat-related and air quality effects. The beneficial effect of blue space on other environmental factors, such as environmental noise, ecological quality and biodiversity, was insufficiently investigated. A better understanding of blue space effects on environmental factors is necessary for it to be used towards microclimate regulation and therefore further research is conducted around this mediating pathway.Research around the relationship between blue space and social interaction is still in its infancy and evidence was mixed. Our systematic review, therefore, presented contrasting evidence for this mediating pathway. Our meta-analyses did not find significant beneficial effects of living closer to blue space  or having more blue space within a geographical area  on social interaction.Findings of this systematic review and meta-analysis are consistent with the existing literature on the salutogenic benefits of blue spaces ,15,83. OHaving reviewed the empirical evidence on the beneficial effect of blue space on the four hypothesised pathways, we suggest that future research should focus on clarifying which particular blue space features have the strongest effect on each mediating pathway. Simultaneously, there is a clear need for more and higher quality research around the effect of blue space on social interaction; research on this lacked consistency and results were found to be inconclusive. This review further highlighted that most studies on the relationship between blue space and environmental factors lacked comparability in terms of outcome measures and failed to account for key confounding factors. Our review highlights the inclusion of more confounding variables in environmental health research, a better definition of blue space elements and the adoption of widely used measures. This is in line with recommendations for future research by Yu et al. , who higThis was a comprehensive review evaluating 50 studies. Our review followed the PRISMA guidelines and had a published protocol. It has also followed guidelines for the composition of systematic reviews in research . The absInterestingly, the search for our systematic review indicated that frequently water bodies are included in existing green spaces categories. Blue spaces are often not separated from green spaces, and simply treated as a category of green spaces. For instance, in a study by Sikorska et al. , water bAs in the case of green spaces , accessi2s ranged between 79.50% and 99.49%. The meta-analysis between amount of blue space and social interaction had a comparatively lower I2 of 56.41%. Potential sources of heterogeneity were the wide range of physical activity and restoration indicators used, differences between study designs and the lack of universal measures of blue space exposure. Thus, high heterogeneity should be expected in this type of research. Results of meta-analyses with high heterogeneity should be considered with caution [High heterogeneity was found in six of our seven meta-analyses conducted for distance to blue space and physical activity, amount of blue space and physical activity, amount of blue space and restoration, distance to blue space and restoration, contact with blue space and restoration and distance to blue space and social interaction. Their I caution . It is lThe overall quality of the articles included in this review was judged to be very good, as no mediating/causal pathway had an average article quality lower than 70%. These quality ratings show promise for research in this sector, as studies have been well-designed.The majority of the articles included in this review had a cross-sectional design (70.00%), followed by longitudinal (14.00%) and cross-over (8.00%) studies. This, together with the recognition that blue space effects are not immediate, but develop over time, may explain why relationships found in our meta-analyses are weak. According to Rindfleisch et al. , a longiArticles included in this review measured exposure to blue space in several ways, which subsequently created compatibility difficulties between articles for our meta-analyses to be conducted. As explained above, the lack of universal measures of blue space exposure led to high heterogeneity in all three meta-analyses. Seventeen different measures of blue space exposure were used in the existing literature, namely 100 m, 300 m and 500 m buffers around residencies, coastal proximity of residencies, access to parks/blue space, the proportion of visible water surfaces, frequency of use using GPS devices, road network access/distance, 1 km circular buffers around residencies, GPS mapping of people’s activities near water, self–assessed distance to blue space, self–assessed use of blue space over time, proportion of blue space per municipality using GIS technology, 5 km buffer around schools, proportion of postcode occupied by blue space, self—assessed visual exposure and participation in activities around blue space, distance of blue space to a neighbourhood, self-perceived distance to blue space, normalised difference water index (NDWI), ratio of “blueness” in street view images, minimal distance to water body and polygons using satellite imaging. As a result, a meta-analysis for each health mediator could not be performed, as very few articles shared the same definition or measurement of blue space exposure. An internationally recognised definition and measurement tool for blue space exposure would improve comparability and allow for quantification and calculation of aggregate effects.Articles related to physical activity used 13 different assessment methods, namely moderate to vigorous physical activity (MVPA), light physical activity (LPA), self-assessed time spent exercising around a blue space per day, self-perceived time spent being active, jogging, recreational walking, watersports, on–land physical activity within 5 km of a blue space, times of walking to work per week, walking more or less than 300 min within a 6.6 km distance to blue space, meeting of physical activity guidelines, health-enhancing energy expenditure per week and percentage of physically active neighbours.Restoration studies mostly used subjective measures, while few studies had more experimental methods. There were 23 different restoration indicators; self-assessed stress, self–assessed attention restoration, self-assessed mental wellbeing, GHQ-12 scores, SF-36 scores, PHQ-9 scores, self–assessed restorative quality, self–reported history of depression, self-reported events of positive/negative mood, self-reported psychological distress, K10 scores, anxiety or mood disorder, history of major depressive disorder, history of use of antidepressants, visits to mental health specialists, stress measurements with EEG devices, self-perceived life satisfaction, WHO-5 wellbeing index, state physical appearance, state body shape, state weight satisfaction, recalled wellbeing and number of self-reported happy moments among children.Articles looking at social interaction used seven different measures, namely self–reported number of visits of blue space with friends, self–reported familiarity with neighbourhood, self–reported sense of neighbouring, self–perceived attachment to neighbourhood, self-reported community participation, self-perceived social appreciation and self –perceived cohesion of neighbourhood. Interestingly, all social interaction measures were self–reported, which might include some personal predisposition and therefore bias. It is as a result, needed for a more neutral tool for social interaction to be established and adopted in future research.Considerable variability was also found in measures of environmental factors as relevant articles used six different environmental measures; air quality (PM2.5), humidity, heat stress index, ecological quality, noise and land surface temperature. Given the nature of the field, no measure was self–reported and all measures were taken using electronic devices or GIS tools. This provides us with robust measurements and any bias should be attributed to malfunction of sensors or range issues.This prominent variability of tools/types within health mediators led to a high degree of methodological heterogeneity in our meta–analyses. On the other hand, the large number of several physical activity, restoration, social interaction measures, as well as environmental factors, prove the complexity of the field and the need for more multidisciplinary research and cooperation.Blue space benefits and use are not equally distributed among people of different age and socio-economic status . Issues This review found a small proportion (16.00%) of articles looking at specific blue features. The amount of knowledge derived from the above eight articles looking at specific blue space features highlights the need for more research in this area and emphasises the need to consider blue space independently from other outdoor environments.The confounding effects of variables such as age, gender, socio-economic status and education were considered in most of the studies included in this review. Indeed, several articles have highlighted the fact that blue space use is dependent on age, with potential differences between children and adults in their interactions with blue space ,40. De BTo our knowledge, two other systematic reviews and a narrative overview have been conducted around the salutogenic effect of blue space ,15,83. TOur review looked deeper into the relationships between blue space and health, including only articles with blue space as an independent environment. This review explored the effect of blue space on the health “mediators”, such as physical activity, restoration, social interaction and environmental factors. To our knowledge, no other systematic review has looked at health mediators, and this review can therefore be considered a logical continuation of the existing narrative overview by White et al.  and systThis systematic review and meta-analysis has summarised and quantified evidence about mechanisms of the salutogenic effect of blue space on health. We found empirical evidence to support three hypothesised pathways. Blue spaces promote physical activity and increase restoration. They also improve environmental factors, however more research is necessary for meta-analyses to be conducted on this third mediating pathway. The evidence about the role of social interaction is ambiguous. Findings for blue spaces are consistent with reported green space benefits. Considering that most cities in the world are built around blue spaces such as coasts, lakes and rivers, blue spaces are potentially valuable public health assets, which may help reduce the health risk factors associated with increased urbanisation.


COVID-19 has disproportionately affected older adults and certain racial and ethnic groups in the United States. Data quantifying the disease burden, as well as describing clinical outcomes during hospitalization among these groups, are needed.We aimed to describe interim COVID-19 hospitalization rates and severe clinical outcomes by age group and race and ethnicity among US veterans by using a multisite surveillance network.We implemented a multisite COVID-19 surveillance platform in 5 Veterans Affairs Medical Centers located in Atlanta, Bronx, Houston, Palo Alto, and Los Angeles, collectively serving more than 396,000 patients annually. From February 27 to July 17, 2020, we actively identified inpatient cases with COVID-19 by screening admitted patients and reviewing their laboratory test results. We then manually abstracted the patients' medical charts for demographics, underlying medical conditions, and clinical outcomes. Furthermore, we calculated hospitalization incidence and incidence rate ratios, as well as relative risk for invasive mechanical ventilation, intensive care unit admission, and case fatality rate after adjusting for age, race and ethnicity, and underlying medical conditions.We identified 621 laboratory-confirmed, hospitalized COVID-19 cases. The median age of the patients was 70 years, with 65.7% (408/621) aged ≥65 years and 94% (584/621) male. Most COVID-19 diagnoses were among non-Hispanic Black  veterans, followed by non-Hispanic White  and Hispanic or Latino  veterans. Hospitalization rates were the highest among veterans who were ≥85 years old, Hispanic or Latino, and non-Hispanic Black . Veterans aged ≥85 years had a 14-fold increased rate of hospitalization compared with those aged 18-29 years (95% CI: 5.7-34.6), whereas Hispanic or Latino and Black veterans had a 4.6- and 4.2-fold increased rate of hospitalization, respectively, compared with non-Hispanic White veterans (95% CI: 3.6-5.9). Overall, 11.6% (72/621) of the patients required invasive mechanical ventilation, 26.6% (165/621) were admitted to the intensive care unit, and 16.9% (105/621) died in the hospital. The adjusted relative risk for invasive mechanical ventilation and admission to the intensive care unit did not differ by age group or race and ethnicity, but veterans aged ≥65 years had a 4.5-fold increased risk of death while hospitalized with COVID-19 compared with those aged <65 years (95% CI: 2.4-8.6).COVID-19 surveillance at the 5 Veterans Affairs Medical Centers across the United States demonstrated higher hospitalization rates and severe outcomes among older veterans, as well as higher hospitalization rates among Hispanic or Latino and non-Hispanic Black veterans than among non-Hispanic White veterans. These findings highlight the need for targeted prevention and timely treatment for veterans, with special attention to older aged, Hispanic or Latino, and non-Hispanic Black veterans. COVID-19 has been found to be more prevalent in older adults, men, and those with certain underlying comorbidities, thereby resulting in higher rates of hospitalization and deaths among these groups . The COVOver 9 million veterans (defined here as former members of the armed forces) are enrolled in the Veterans Affairs (VA)–integrated health care program . These USUPERNOVA sites served 396,280 unique veterans in outpatient and inpatient settings in the fiscal year 2019 . The veteran catchment population at these sites was 32%  non-Hispanic Black, 47%  non-Hispanic White, and 11%  Hispanic or Latino. The overall median age of the veterans in the catchment population was 64 years, and 87%  of all veterans were male.To identify eligible patients for COVID-19 surveillance, trained research personnel screened admission logs and diagnoses , lists oHospitalization incidence per 100,000 person-years among veterans was calculated based on previously published methods by using the catchment population of unique individuals served at each facility . Severe P<.05.Case fatality rate (CFR) was calculated as a 14-day moving average. We plotted the distribution of cases and compared the CFR over 2 time periods: one early during the pandemic and one later in the summer months. Patients who were still hospitalized were excluded from the analysis. Differences between groups and time periods were compared by chi-square tests and considered significant if This study was reviewed, informed consent was waived, and a final approval was obtained by 5 VA sites, research and development committees, and the Centers for Disease Control and Prevention institutional review board(s).P<.01).From February 27 through July 17, 2020, a total of 621 laboratory-confirmed, hospitalized COVID-19 cases were identified at the 5 VAMCs. As of July 31, 2020, 27 of the 621 (4.3%) patients continued to remain hospitalized. These cases initially peaked in late March and April 2020, before declining and then plateauing in May and June, and then increased again in the latter half of June and early July, with the highest peak in new hospital admissions recorded on July 1, 2020 . The CFRThe Bronx VAMC had the highest number of hospitalized veterans diagnosed with COVID-19 , followed by Atlanta , Houston , Los Angeles , and Palo Alto . Across all VAMCs, the patients’ median age was 70 years, with 66% (408/621) of the patients aged ≥65 years and 94% (584/621), male. The highest percentage of hospitalizations due to confirmed COVID-19 diagnoses were among non-Hispanic Black veterans , followed by non-Hispanic White , Hispanic or Latino , non-Hispanic Asian , non-Hispanic American Indian or Alaskan Native , and non-Hispanic Native Hawaiian or Pacific Islander  veterans. About 2.4% (15/621) of all veterans had an unknown race or ethnicity.The overall hospitalization rate was 205.7 per 100,000 population . HospitaOverall, 11.6% (72/621) of the patients required invasive mechanical ventilation, 26.6% (165/621) were admitted to the intensive care unit (ICU), and 16.9% (105/621) died while hospitalized . AlthougP=.001), COPD , coronary artery disease , heart failure , hypertension , and diabetes . Veterans aged <65 years had a higher prevalence of obesity than those aged ≥65 years . By race and ethnicity, non-Hispanic Black veterans  had a higher prevalence of chronic kidney disease than Hispanic or Latino  and non-Hispanic White veterans , whereas non-Hispanic White veterans had a higher prevalence of COPD .Most patients had at least one of the 7 underlying medical conditions  . By age The burden of COVID-19 hospitalizations at these 5 VAMCs was the highest among older, Hispanic or Latino, and non-Hispanic Black veterans. Veterans aged ≥50 years had a higher rate of hospitalization than those aged 18-29 years, and Hispanic or Latino and non-Hispanic Black veterans had a 4.6- and 4.2-fold higher rate of hospitalization, respectively, than non-Hispanic White veterans. More severe outcomes were noted among older adults, with 9 out of every 10 deaths reported among those who were aged ≥65 years. Moreover, these older veterans also had a 4.5-fold increased risk of death following hospitalization with COVID-19 as compared to those aged <65 years. These findings highlight the need for targeted prevention, control and treatment efforts for veterans, with special attention to increasing age and race and ethnicity .Our COVID-19 surveillance data demonstrated that Hispanic or Latino and non-Hispanic Black veterans were hospitalized for COVID-19 at higher rates than were non-Hispanic White veterans, which is consistent with the findings of studies in the United States and other countries ,12. DespSimilar to nationwide death certificate trends, we observed a decline in the CFR since the start of the pandemic . ContinuNearly all patients (88.1%) in this cohort had an underlying medical condition, and veterans aged ≥65 years had higher prevalence of several key comorbidities. Many studies have indicated the heightened risk of both older age and specific underlying medical conditions  for severe COVID-19 outcomes, including hospitalization, ICU admission, mechanical ventilation, and death ,18. VeteThis study has limitations. First, early during the pandemic, limited COVID-19 testing was conducted nationwide, and this may have led to an under-ascertainment of patients with COVID-19. Second, although prior studies have indicated that 91% of veterans enrolled in VA healthcare in these 5 site catchment areas use their local VAMCs for care [In conclusion, multisite COVID-19 surveillance conducted at 5 VAMCs across the United States from February 27 to July 17, 2020, demonstrated higher hospitalization rates and more deaths among older veterans as well as higher hospitalization rates among Hispanic or Latino and non-Hispanic Black veterans than among non-Hispanic White veterans. To prevent contracting and spreading COVID-19, veterans and persons living with them should follow recommendations such as practicing social and physical distancing, regularly washing hands, and wearing masks, including inside the house. From a systems-level perspective, policies and procedures that focus on veterans, including timely and high-quality care as well as access to therapeutics and future vaccines, will help protect this population and reduce morbidity and mortality therein. Ongoing data collection at these sites will aid in further characterizing the clinical characteristics of COVID-19, better understanding the risk factors and management of hospitalized patients, characterization of the immune response to SARS-CoV-2 infection through collection of patients’ serum samples, and description of long-term outcomes following hospitalization.


To estimate the prognostic relevance of human papillomavirus (HPV) 16 and HPV 18 in patients with cervical cancer.We searched PubMed, EMBASE, American Society of Clinical Oncology (ASCO) and the European Society of Medical Oncology (ESMO), CNKI, and Wanfang databases to search primary articles illustrating the survival outcomes in cervical cancer patients with or without HPV 16/18 infection. A meta-analysis was conducted to generate a combined hazard ratio (HR) with 95% confidence intervals (CI) for progression-free survival (PFS), disease free survival (DFS) and overall survival (OS).P = 0.44). Cervical cancer patiensts infected with HPV 18 had worse OS , DFS  and worse PFS  compared with those not infected with HPV 18. cervical cancer patiensts infected with HPV 18 had worse PFS compared with those infected with HPV 16 .A total of 13 studies were included. Our meta-analysis revealed that HPV 16 positive did not have any impact on OS (HR, 0.76; 95% CI = 0.37–1.54; Cervical cancer patients infected with HPV 18 had worse survival compared with cervical cancer patients with HPV 16 infection. Cervical cancer occurs in the cells of the cervix, with highest incidence rates found among women between 40 and 60 years old. Cervical cancer is the second most common female cancer worldwide . The preP = 0.02) [Several factors would impact the prognosis for cervical cancer patients, such as tumor staging, size and metastatis. Although the effect of HPV on the development of cervical cancer has been well eastablished, its function of prognosis is still not well understood. Several studies have found the prognosis role of HPV 18 infections in early stage cervical cancer patients , 11, 18. = 0.02) . However = 0.02) . A brazi = 0.02) .P = 0.005) [P = 0.033) [P = 0.06) [The prognostic impact of HPV 16 on survival in patients with cervical cancer is also controversial –7, 9. AlThus, we performed an updated systematic review and meta-analysis to summarize the impact of HPV 16 and HPV 18 on survival in patients with cervical cancer.PubMed, EMBASE, American Society of Clinical Oncology (ASCO) and the European Society of Medical Oncology (ESMO), CNKI, and Wanfang databases were searched by our researchers using common keywords related to HPV 16, HPV 18, cervical cancer and survival. The following keywords were included: human papillomavirus 16, human papillomavirus 18, cervical cancer, DFS, PFS and OS. We reviewed the details of these relevant publications for additional papers.We selected articles that met the following criteria: (1) the clinical study recruited patients with pathologically or cytologically diagnosed cervical cancer; (2) the clinical study investigated survival related results, such as PFS, DFS and OS with a HR and 95% CI.Two independent researchers in our department read all the publications independently and discussed the study extraction until they reached consensus. The criterias defined by Cochrane Handbook for Systematic Reviews of Interventions version 5.1.0 were used , the fol2 statistic. We considered an I2 value > 50% to indicate a significant heterogeneity between these studies. A random effects model was used if significant heterogeneity was detected among studies. If I2 value was below 50%, results were measured using a fixed effects model.We chose PFS, DFS and OS as the endpoints in our meta-analysis. The survival data associated with HPV 16 and HPV 18 were summarized in Tables In total, 13 eligible studies were included in this systematic review and meta-analysis, with 6 trials about the survival data of cervical cancer patients infected with HPV 16 and 7 trials about the survival data of cervical cancer infected with HPV 18. Among these publications, 3 publications investigated the impact of both HPV 16 and HPV 18 on survival in cervical cancer patients. Three publications investigated the impact of both HPV 16 and HPV 18 on survival in cervical cancer patients. A flow chart of selection of the studies is illustrated in Fig. P = 0.44, Fig. We identified 4 eligible trials  includinP = 0.0001, Fig. We identified 4 eligible trials , 11, 13 P < 0.0001, Fig. We identified 3 eligible trials , 9, 11 iP = 0.00012, Fig. We identified 2 eligible trials , 12 inclP = 0.01, Fig. We identified 3 eligible trials –22 incluP > 0.05) and Begg’s test (P > 0.05).No evidence of publication bias was found in our study by funnel plot, Egger’s test (Our study was the first systematic review and meta analysis investigating the impact of HPV 16 and HPV 18 on survival in cervical cancer patients. Our results indicated that patients infected with HPV 18 had worse DFS, PFS and OS compared with cervical cancer patients without HPV 18 infection. While the infection of HPV 16 had no impact on survival in cervical cancer patients compared with all other patients. Cervical cancer patients with HPV 18 infection had worse OS in comparision with patients with HPV 16 infection.An ongoing HPV infection could be a risk factor of infection of another HPV genotype , 24 and P = 0.0001, Fig. P < 0.0001, Fig. P = 0.00012, Fig. P = 0.01, Fig. During the development and progression of cervical cancer, patients could be infected with many genotypes of HPV, including high, intermediate and low risk HPV. However, more publications indicating the negative impact of HPV 16 or HPV 18 on survival in cervical cancer patients , 29. TheAwareness of the HPV 16 or 18 infection should be raised when it can be controlled during the disease progression. However, for HPV infection, that is not the case. There is no specific medicines to treat HPV infection. The good news is that patients’ immune system could clear 90% of the HPV infection within 2 years, as long as people with normal immunity . For theWe must admit that our meta analysis has several limitations. Firstly, some of the studies recruited in our meta analysis did not have a large sample size, which would ruin the power of statistics. Secondly, the prognostic relavance of HPV 16 or 18 in some studies are not validated using a multivariate analysis considering the impact of confounding factors, such as tumor size, clinical stage and metastasis. Thirdly, these studies recruited a broad spectrum of patients, range from stage I to stage IV patients, which could raise the heterogeneity of the meta analysis. We were not able to get more data about patients with multiple infection of HPV genotypes, such as treatment. Treatment has an impact on the HPV infection, for example, HPV 18 is more resistant to radiotherapy. There are not many studies published comparing the survival relevance of HPV 16 to HPV 18, thus we were not able to make subgroup analyses based on different treatment, such as adjuvant chemotherapy or radiotherapy. We summarized the treatment methods in Table Cervical cancer patients infected with HPV 18 had worse survival in comparision to patients with HPV 16 infection.


A major challenge in human papillomavirus (HPV) vaccine programs is the universal gender-neutral recommendation, as well as estimation of its long-term effect. The objective of this study is to predict the added benefit of male vaccination, especially in men who have sex with men (MSM), and to analyze the impact of the program on society. We propose a mathematical model of the HPV infection based on a network paradigm. Data from Spain allowed constructing the sexual network. HPV force of infection was taken from literature. Different scenarios using variable vaccine coverage in both males and females were studied. Strong herd immunity is shown in the heterosexual population, with an important decrease of HPV 6/11 infections both in men and in unvaccinated women with an only-women vaccination at 14 years of age. No impact of this program occurred in the infection incidence in MSM. This group would only benefit from a vaccination program that includes males. However, the impact at short term would be lower than in heterosexual men. The protection of MSM can only be achieved by direct vaccination of males. This may have important consequences for public health. Disparities in cancer burden between different populations, including differences associated with sexual orientation are well known. Many agencies work to identify and address the factors that lead to health inequalities . RegardiThe HPV infection also increases the risk of other cancers as anogenital tract and oral cavity in both males and females ,4 and coThe coverage with ≥1 dose of HPV vaccine, and the percentage of adolescents who were up to date with the HPV vaccination series increased in 2019 and both measures improved among females and males ,8,9, butThere is therefore a marginal benefit of vaccinating males and this practice might not be cost-effective ,15,16. HRecent reports have noted increasing rates of anal and oral cavity and pharynx cancer among high-income countries worldwide ,25,26,27The effectiveness of HPV vaccination programs can be affected by different factors related with the sexual behavior, age difference between sexual partners .A vaccination program targeting MSM may have low benefit as most of them would have been infected already at the time of vaccination , when thDuring the past decade, many models have been developed to understand HPV infection epidemiology and to help guide policy decisions regarding vaccination  and are The objective of the study is to estimate by lifetime sexual partners (LSP) network mathematical modeling, the impact of a gender-neutral vaccination program on the HPV infection, focusing on the impact on MSM, with current vaccine coverage in Spain (about 70% in adolescents).The sexual network consists of nodes  and links or bonds between partners representing contacts where the infection may spread. Using this network, it is possible to simulate the evolution of transmission of an infectious disease over time. In network models, we can follow any individual and select those targets for a vaccination program, which is more difficult in continuous models.For the construction of the sexual network, as there is no complete information on the sexual behaviors in a society, we assumed that a large-scale network of sexual contacts would be similar to a random network, where individuals or node bonds are assigned at random, but taking into account some similarities among individuals related to age and promiscuity. Data on sexual behavior specific from Spain were collected from the Health and Sexual Habits Survey 2003 .MSM population represent 3.88% of the total male population in Spain  and wereThis model takes into account infections by the most common genotypes in Spain and has been calibrated and simulated for HPV genotypes that cause cancer and genotypes that cause genital warts (HPV 6/11), all covered by nine-valent vaccine.Infections are simulated with a susceptible-infectious-susceptible (SIS) model in which every node/individual may be susceptible or infected by HPV.The global frequencies of the intercourses per age group and time step.The average recovery time from HPV 6/11 infection.Two parameters determining if the HPV 6/11 infection is transmitted from a man or woman to his/her partner (force of infection).A set of probabilities were considered and calibrated to explain the transitions among SIS states:To calibrate the model, we used data from the CLEOPATRE study  in whichThe network consisted of 100,000 nodes, and the vaccine effectiveness was assumed to be 96.5% in naïve subjects of both genders, and between 20% and 54% in MSM when requiring vaccination .The population modelled were all persons 14 to 64 years of age, so when each member of the community enters the model, they were already vaccinated depending on the vaccine coverage. The temporal length of the model was 100 years, and each temporal step corresponded to one calendar month.Scenario 1: Only girls were vaccinated with a coverage of 70% (current vaccination program in Spain).Scenario 2: 70% of both girls and boys were vaccinated.Scenario 3: 70% of girls were vaccinated and 20% of MSM 18 to 45 years starting 15 years after the girls’ program (to resemble most of the programs).We assessed different scenarios:t is the decline of the HPV infections in the time instant t, Pt is the prevalence of the HPV infection in the time instant t and P is the prevalence of the HPV infection with no vaccination program.We calculated the decline of the prevalence of HPV infection on women, overall men and MSM over time measured ast is the percentage of HPV infections averted in the time instant t, Pt is the prevalence of the HPV infection in the time instant t in scenario 1 or 2 and Nt is the prevalence of the HPV infection in the non-vaccination scenario.To estimate the percentage of HPV infections averted in both scenarios, we compared the prevalence of infection at a moment with a non-vaccination scenario and use the formulaTaking into account the short period of time in developing genital warts when infected by HPV 6/11 (6 months), we can assume that HPV 6/11 decline (percentage of averted cases) is similar to decline (percentage of averted cases) in genital warts.As sexual behaviors are continuously changing; we increased the percentage of MSM to 10%. That implied an increase in the number of LSPs of MSM around 160% compared to the case base.The effectiveness of the vaccine when used in MSM was considered between 20 and 54%, therefore two models of maximum and minimum effectiveness were described.To avoid the inconveniences of having data on sexual behavior specific from Spain of 2003, we have published a model sensitivity analysis, we found that large changes in the sexual behavior, in some extent, only have minor effects on the decline of the HPV infections in women and men in the current vaccination campaign in Spain (vaccination of young girls with a coverage of 70%) .Network mathematical models is a path forward in the modeling of the epidemiology of infectious diseases. We used this model to predict the epidemiology of respiratory syncytial virus (RSV) in babies and toddlers , and witThe sexual network model here presented has already been used to study the epidemiology of HPV infection before and after vaccination and reflected the fast decline of genital warts in Australia after the immunization campaign ,36. A vaShortly after the implementation of the only girls’ vaccination program, there is a large impact on the transmission of HPV 6/11 genotypes with a reduction of HPV infections in both women and men a,c. ThatThe vaccination of women only (Scenario 1) does not affect HPV infection amongst MSM c. Only wTargeted vaccination programs do not seem to be effective. In Results about the percentage of averted HPV 6/11 infections are shown in Case base. This is the current situation, with the percentage of MSM equal to 3.88%, and the current program to vaccinate young girls with a coverage of 70%.Case 1. It is the case base increasing the percentage of MSM up to 10%.We propose the following scenarios to be simulated in order to perform a sensitivity analysis:The increase of MSM up to 10% implies an increase in the number of LSPs of MSM around 160%, compared to the case base.Prophylactic HPV vaccine programs constitute major public health initiatives worldwide and modelling studies have been and still are widely used to inform HPV vaccination policy decisions , the anaUsing LSP network models  could haOur findings are in agreement with those found by Brisson, et al. , on the In this way, our study is also consistent with the modeling carried out by Bogaards J. et al.  for MSM Our model suggest that elimination of HPV 6/11, is likely if vaccination coverage of girls and boys reaches 70% and the vaccine provides long-term protection.On the other hand, we modeled a scenario with a target vaccination program for MSM. We found no changes in the evolution of HPV infection in this group. There were no changes in the decline of the infection even after increasing the vaccination coverage, in contrast to Gao S. et al. , who sugInformation on sexual orientation disparities in cancer incidence and mortality is not available for the general population, and in general is mostly inferred from populations with HIV/AIDS , mainly In this study, we showed that having a universal vaccination program for both girls and boys will have an important effect on the epidemiology of HPV cancers. Moreover, even with a persistent 70% vaccine coverage in the current vaccination programs, the infection will persist in the MSM population as current models do not achieve correct protection of this subgroup of the population.In this work we have analyzed the community effect for HPV 6/11 vaccination in Spain. Also, other scenarios have been analyzed in order to assess the impact of a gender neutral vaccination program on MSM.To achieve this objective, we have applied a recent model for the network of sexual contacts in a population that can be calibrated by modifying the number of lifetime sexual partners according to new evidence or to create new simulations. This mathematical model based upon the network paradigm has been successfully used to study the stable number of HPV infections  as well In the particular case of Spain, we have found in the near future the community effect will be very evident for the male population, with a decline in the percentage of cases, approximately, the double of the percentage of cases directly prevented in females as a consequence of vaccination. The results in the female population show a more likely improvement, but at the very least the current levels of protection will be sustained.This data corresponds with a simulation on the population of Spain for a sustained vaccination campaign keeping a coverage around 70% for girls aged 14 years old. Our study has also spotted an important handicap of the present vaccination program that implies low or null community effect in the MSM population. One of the possible causes for this result may be due to the greater number of sexual partners, in which part of this group may have events with women, as has also been described for this group of the population in other countries .This may have important consequences for public health policies as it is a question under discussion at the moment the inclusion in the vaccination campaigns. To evaluate this second scenario, we have studied the effect of 70% coverage in both boys and girls to analyze the number of averted cases of genital warts directly caused by HPV 6/11 infections. The improvement for heterosexual men is more or less doubled in the following decades with a protection of MSM as well. For these reasons, the recommendation of boys’ vaccination with the HPV vaccine is supported by these results.There are many possible combinations to create networks fulfilling the requirements in The computational network model developed depends on the data used in its construction. Thus, it will be influenced by possible biases in the data about sexual behavior  and the The lack of specific data about sexual behavior of the population do not allow us to check the reliability of the network structure. However, the computational network model built reproduces accurately real situations .Our analysis did not include scenarios with naturally acquired immunity or reactivation of latent infections since the mechanisms of immunity and latency are not well understood yet.The sexual network model built predicted that the vaccination of only women leaves MSM without protection and informs that their protection can only be achieved by the direct vaccination of males. This may have important consequences on public health.


Cervical cancer is caused by persistent infection with oncogenic, or“high-risk” types of human papillomaviruses, and is the most commonmalignancy in Kenyan women. A longitudinal study was initiated toinvestigate factors associated with persistent human papillomavirusdetection among HIV-infected and HIV-uninfected Kenyan women withoutevidence of cervical dysplasia.Demographic/behavioral data and cervical swabs were collected fromHIV-uninfected women (n = 82) and HIV-infected women (n = 101) at enrollmentand annually for 2 years. Human papillomavirus typing was performed on swabs(Roche Linear Array). Logistic regression models of human papillomaviruspersistence were adjusted for demographic and behavioralcharacteristics.HIV-infected women were older and less likely to be married and to own a homeand had more lifetime sexual partners than HIV-uninfected women. AllHIV-infected women were receiving anti-retroviral therapy at enrollment andhad satisfactory CD4 cell counts and HIV viral loads. One- and two-yearpersistent human papillomavirus detection was significantly associated withHIV infection for any human papillomavirus, high-risk human papillomavirus,International Agency for the Research on Cancer-classified high-risk humanpapillomavirus, and non-oncogenic “low-risk” human papillomavirus.Persistent detection of oncogenic and non-oncogenic human papillomavirus wasstrongly associated with HIV infection in Kenyan women with re-constitutedimmune systems based on satisfactory CD4 cell counts. In addition to HIVinfection, factors associated with an increased risk of human papillomaviruspersistence included a higher number of lifetime sex partners. Factorsassociated with decreased risk of human papillomavirus persistence includedolder age and being married. Further studies are needed to identify theimmunological defects in HIV-infected women that allow human papillomaviruspersistence, even in women receiving effective anti-retroviral therapy.Further studies are also needed to determine the significance of low-riskhuman papillomavirus persistence in HIV-infected women. In addition, while HIV-induced immunosuppression accountsfor much of the increased incidence of cervical, other co-factors may beimportant.In spite of advances in cervical cancer screening and HPV vaccine development, manyquestions about HPV in HIV-infected women remain unanswered. In contrast to thedecline of other HIV-associated cancers (Kaposi sarcoma and B-cell lymphoma) sinceanti-retroviral therapy (ART) became available, the incidence of cervical cancer hasnot declined.25 A longitudinal study was, therefore, conducted to identify potentiallymodifiable behavioral and biological factors associated with persistence.A previous analysis of this cohort at study enrollment showed that HR-HPV types weremore frequently detected in HIV-infected women compared to HIV-uninfected women.Study approval was granted from the Moi Teaching Referral Hospital (MTRH) and MoiUniversity School of Medicine, Eldoret, Kenya, the Kenya Medical ResearchInstitute’s Scientific and Ethics Review Unit (KEMRI-SERU), and theInstitutional Review Board of Indiana University School of Medicine. All studyparticipants received a written copy of the consent (English or Swahili).38This was a prospective cohort study conducted in Eldoret, Kenya, to identifypotentially modifiable behavioral and biological factors associated withpersistence of HPV in HIV-infected and HIV-uninfected women. These women wererecruited at the Academic Model Providing Access to Healthcare (AMPATH) CervicalCancer Screening Program at MTRH.25A balanced (HIV-infected/-uninfected) cohort of women aged 18 to 45 years livingwithin 30 km of Eldoret was recruited. These women had no evidence of cervicaldisease based on visual inspection with acetic acid (VIA) at enrollment. Anenrollment of 220 participants was planned. To achieve a balance of 50%HIV-infected and 50% HIV-uninfected, women with normal VIA examinations wereinvited to participate in a sequential manner. Because approximately 60%–65% ofwomen presenting to the clinic have been HIV-infected in recent years, it wasexpected that the goal of 110 HIV-infected women would be reached before theenrollment of 110 HIV-uninfected women. Therefore, when 110 HIV-infected womenwere enrolled, approximately 90 HIV-uninfected women were enrolled, and onlyHIV-uninfected women were invited to participate from that point on until theplanned 110 HIV-uninfected were enrolled. However, due to several extra womenbeing enrolled, some women eventually not agreeing to participate, and somewomen eventually being excluded, the final overall study included 106HIV-uninfected and 116 HIV-infected women.For inclusion into this analysis of HPV persistence, a participant’s enrollmentcervical swab and at least one swab from the Year 1 or Year 2 visits had to beavailable. A total number of 183 women, including 82 HIV-uninfected and 101HIV-infected women, had such swabs performed and were therefore included in theanalysis.Chlamydia trachomatis orNeisseria gonorrhoeae, current pregnancy, inability toconsent, or medical illness rendering the participant unable to attend visits.Participants were provided phone credit to contact study nurses if needed andwere compensated for their time and effort at each visit as described.25Exclusion criteria included abnormal VIA, a history of an abnormal VIA or Papsmear, previous diagnosis of cervical intraepithelial lesion (CIN) or cervicalcancer, signs or symptoms of 25 In addition, we had expected persistent HPV detections during thelongitudinal follow-up would be approximately 45% among HIV-infected women and20% among HIV-uninfected women. Our sample size of 222 participants provided 85%power to detect a 20% difference in HPV detection and 98% power to detect a 25%difference in persistent HPV detection between HIV-infected and HIV-uninfectedwomen based on chi-square tests at a two-sided 0.05 significance level. Despiteloss of follow-ups in the longitudinal study, our analytical sample size of 183women (101 HIV-infected women and 82 HIV-uninfected women) still provided a 95%power to detect a 25% difference in persistent HPV detection betweenHIV-infected and HIV-uninfected women.The sample size of this study was chosen to ensure sufficient power to addressthe specific research questions. It was expected that approximately 60% ofHIV-infected women and 40% of HIV-uninfected women would have HPV detected inannually collected cervical swabs during the longitudinal study. The actual HPVdetections in our study sample was 59.1% among HIV-infected women and 35.2%among HIV-uninfected women at enrollment.25 Women were followed for 2 years with clinic visits every 12 months forthis analysis. At enrollment, Year 1, and Year 2, a nurse or physician collecteda cervical swab for HPV testing as part of the pelvic examination. Swabs wereplaced in standard transport media then frozen at −80°C. For HIV-infected women,variables were collected from the AMPATH Medical Record System including date ofHIV diagnosis, ART use, HIV viral loads, and CD4 cell counts.Structured face-to-face interviews by trained researchers were conducted atenrollment as previously described, and a brief questionnaire was utilized togather certain demographic and behavioral information.Per Kenya standard of care, all women were asked to return annually for VIA inthe AMPATH Clinic. There are no guidelines in Kenya for specific treatmentrelated to HR-HPV detection, whether incident or persistent, so no specificchanges in treatment were recommended based on HPV findings.25 The Roche Linear Array  was used to determine HPV types as previously described.39 For the purpose of analysis, the 37 HPV types detected in the RocheLinear Array Assay were divided into four groups: Any  HPV types, HR-HPV,International Agency for the Research on Cancer (IARC) HR-HPV types, asdesignated by the IARC,40 or LR-HPV. Individual types assigned to these groups are shown at thebottom of Specimens were transported to the Kenya Medical Research Institute–University ofMassachusetts Medical School laboratory for processing as previously described.Persistent HPV detection was defined in two ways: first, at the level oftype-specific HPV records and second, to confirm the results of the firstanalysis and to provide an analysis in a clinically relevant format at the levelof study participants. At the level of type-specific persistent HPV detectionrecords, four “detection patterns” for each type-specific HPV in swabs weredefined:Pattern 1: no type-specific HPV detection in swabs at enrollment orfollow-up visits.Pattern 2: Non-persistent detection: a positive type-specific HPVdetection in only one swab sample.Pattern 3: 1-year persistent detection: a positive type-specific HPVdetection in two consecutive swabs.Pattern 4: 2-year persistent detection: a positive type-specific HPVdetection in swabs obtained 2 years apart.Hypothetical examples illustrate how persistence was determined at thetype-specific persistent detection level. A participant may have had HPV 16detected at enrollment, but not at Year 1 or Year 2. This would representnon-persistent detection (Pattern 2) for HPV 16. In addition, she may have hadHPV 45 detected at all three visits, representing a 2-year persistent detection(Pattern 4) for HPV 45. If no other HPV types were detected, these types wouldeach be assigned “no detection” (Pattern 1). Altogether there were 183women × 37 HPV types = 6771 type-specific persistent HPV detection records (3034records from HIV-uninfected women and 3737 from HIV-infected women).Persistent HPV detection was also defined at the level of study participants,defined as the highest level of persistent detection pattern in the descendingorder of “2-year persistent detection,” “1-year persistent detection,”“non-persistent detection,” and “no detection” among a woman’s type-specific HPVdetection records within a group . Forexample, a participant may have had HPV types 18 and 33 detected at enrollment,and HPV 33 at Year 1 but not Year 2. No other HPV types were detected. Thisparticipant thus had “1-year persistent detection” for HPV 33 and“non-persistent detection” for HPV 18, and she would be classified as “1-yearpersistent detection” for any HPV types, HR-HPV types, and IARC HR-HPV types dueto her highest persistent detection level from HPV 33. For LR-HPV types, shewould be classified as “no detection.”Demographic and behavioral characteristics of participants at enrollment  weresummarized by descriptive statistics and compared betweenHIV-infected/uninfected women using t-tests, chi-square tests, or Wilcoxon ranksum tests. CD4 counts and HIV viral loads at enrollment and follow-up visitswere reported for HIV-infected women. Patterns of “1-year persistent detection”and “2-year persistent detection” were then combined together as “persistentdetection” for subsequent analysis. Counts and percentages of the five mostfrequently detected HR- and LR-HPV types in HIV-infected and HIV-uninfectedwomen were reported.Logistic regression models were fit to examine the associations between overallHPV detection (“non-persistent detection” and/or “1-year persistent detection”and/or “2-year persistent detection” vs “no detection”) and HIV status at thetype-specific detection records level and at the study participant levelseparately. Furthermore, logistic regression models were fit to examineassociations between persistent HPV detection (“1-year persistent detection”and/or “2-year persistent detection” vs “no detection” and/or “non-persistentdetection”) and HIV status at the type-specific detection records level and atthe study participant levels separately. The generalized estimating equationmethod was used in the regression models at the level of type-specific detectionrecords to account for the correlations between multiple records from the sameparticipant.In addition, associations of CD4 cell counts with HPV persistence were examinedamong HIV-infected women using logistic regression models performed at the levelof study participants. HIV-infected women were classified into four categoriesbased on CD4 counts at enrollment: ⩽200, 201–350, 351–500, and >500 cells/µL.The risk of persistent HPV detection (1-year persistent and/or 2-year persistentdetections) was compared between women who had the lowest CD4 counts(⩽200 cells/µL) with women who had higher CD4 counts. Demographic and behavioralcharacteristics were included in all logistic regression models as potentialconfounders. Analyses were performed using SAS Version 9.4 .Of the 82 HIV-uninfected women, 58 (70.7%) attended all three visits, 8 (9.8%)attended the Enrollment plus Year 1 visits, and 16 (19.5%) attended theEnrollment plus Year 2 visits. For the 101 HIV-infected women, 77 (76.2%)attended all three visits, 15 (14.9%) attended the Enrollment plus Year 1visits, and 9 (8.9%) attended the Enrollment plus Year 2 visits (p = 0.089).A comparison of women in the analytic sample (n = 183) and women excluded due toloss of follow-up (n = 39) showed that women excluded were younger than theremaining women , but no significantdifferences were found in HIV status, marital status, education level, homeownership, walking distance to health care, number of lifetime sexual partners,or age of first sexual experience. Compared to HIV-uninfected women,HIV-infected women were significantly older and less likely to be married or toown a home, had more lifetime sexual partners, and had a lower age of firstsexual intercourse .All 101 HIV-infected women were receiving ART at enrollment. The initiation dateof ART was available in medical records for 93 of these 101 HIV-infected women;the mean duration of ART use for these 93 women was 4.3 years . The medFor all cervical swabs from all women, >99% were adequate based on positiveβ-globin results. The most frequently detected HR-HPV types throughout the studywere HPV 16, 51, 58, 59, and 66; the most frequently detected LR-HPV types wereHPV 54, 61, 62, 83, and 84 . For eacHPV detection patterns were analyzed by HIV status at the type-specific HPVdetection records level and at the study participant level . In theLogistic regression analysis was conducted to assess associations of overall HPVdetection with HIV status and other characteristics of women in the longitudinalstudy . Inthe Logistic regression analysis of associations of persistent HPV detection (1 yearand 2 year) with HIV status and characteristics of women was performed . AnalysiThe risk of persistent HPV detection (1- and/or 2-year persistent detections) wascompared between HIV-infected women who had the lowest CD4 counts(⩽200 cells/µL) and those with higher CD4 counts. Regression models demonstratedthat women with the lowest CD4 counts had a higher likelihood of HR-HPVpersistence than women with higher CD4 counts . As it w4146 This study confirmed that alltypes of HPV are common and detected more often in HIV-infected Kenyan women than inHIV-uninfected women. Most importantly, persistence of all groups of HPV  was associated with HIV infection. TheORs for HR-HPV persistence was approximately 2.5 for being HIV-infected and 27 forLR-HPV persistence, in spite of good adherence to ART and good immune functionwithin the HIV-infected cohort. Even when those with the lowest CD4 counts wereeliminated from the analysis, HIV-infected women still had significantly more HPVpersistence than HIV-uninfected women. Because persistent HPV infections were socommon in this cohort of HIV-infected women, most of whom were receiving ART and had“re-constituted” immune systems, it is likely that unidentified components of theimmune system are necessary for control of HPV infections.Most studies of HPV infection among sub-Saharan African women have beencross-sectional, indicating that HR- and LR-HPV infections are common and thatHIV-infected women have a higher rate of HPV detection compared to HIV-uninfectedwomen.47 found that 6-month persistent infections were more common in HIV-infectedNigerian women compared to HIV-uninfected women. ORs comparing HIV-infected andHIV-uninfected women were not significant for persistent LR-HPV detection. ForHR-HPV, the OR was 4.49 (95% CI 2.26–8.91) for persistent detection. Somedifferences between this study and the study by Adebamowo et al. include a differentHPV detection system , a shorter follow-up time in the study byAdebamowo et al. (6 vs 24 months), and a lack of ART data for the HIV-infectedcohort in the study by Adebamowo et al. Mukanyangezi et al.48 studied HPV detection in 100 HIV-uninfected and 137 HIV-infected women livingin Rwanda over a 24-month period. Persistent HR-HPV but not LR-HPV occurred moreoften among HIV-infected women than in HIV-uninfected women. It was not clear howpersistence was defined, and no data on ART use were available.Few prior studies of HPV persistence in HIV-infected women have been conducted amongwomen living in Africa. Adebamowo et al.49 examined associations of HR-HPV detection and persistence with high-gradecervical intraepithelial neoplasia (CIN2+) in HIV-infected women living in BurkinaFaso or South Africa. In contrast to this study, there was no HIV-uninfected controlgroup of women. HPV typing of cervical swabs was performed at enrollment and at asecond visit, 16 months later. Of 270 women living in Burkina Faso, 59.1% had16-month persistence of a HR-HPV type, HPV 58 being the most frequently detectedpersistent type. Of 340 women living in South Africa, 44.7% had 16-month persistenceof a HR-HPV type, HPV 35 being the most frequently detected persistent type.Persistence of any HR-HPV, HPV 16 plus HPV 18 combined, or HR types HPV 31, 33, 45,52, and 58 combined were associated with development of CIN2+.Kelly et al.50 assessed the impact of ART on persistent HR-HPV infection in 652 HIV-infectedwomen living in Belgium, 84% of whom were from sub-Saharan Africa and 79% werereceiving ART. HR-HPV was detected in 43% of women. Sustained HIV suppression andCD4 cell counts >500 cells/µL for >18 months were associated with decreasedrisk of persistent HR-HPV infection. Thorsteinsson et al.13 assessed risk factors of HR-HPV persistence among 71 HIV-infected womenliving in Denmark. Persistent HR-HPV detection occurred in 31 (43.7%) women. A CD4count of <350 cells/μL predicted HR-HPV persistence. The ACTG A5029 trialfollowed 146 HIV-infected women prospectively after starting ART.51 Detection of most HPV types decreased over the 96 weeks of the study; HR-HPVdetection decreased from 62% to 39%.Several prior studies of HIV-infected women living in North America or Europe alsoindicate a high degree of HPV persistence, but as with the study by Kelly et al.mentioned above either did not include an HIV-uninfected control group or details ofART use were not reported. Konopnicki et al.The risk of LR-HPV type persistence was higher in HIV-infected women compared toHIV-uninfected women. The significance of this observation is not known, but whileHR-HPV types account for the majority of cervical cancers worldwide, it is possiblethat LR-HPV types may be more pathogenic in HIV-infected women, especially the typesthat were once considered “intermediate risk” types by IARC. Further studies areneeded to clarify this issue.Limitations of this study include a modest number of women enrolled, although eachparticipant was sampled repeatedly, providing additional statistical power. Thesampling method utilized could reduce the generalizability of the findings. Becausemost HIV-infected women were receiving ART, it was not possible to perform a directcomparison of women receiving ART versus women not receiving ART to determine thedirect effect on reducing HPV persistence. As this study progresses, the effects ofspecific HIV-related variables (including the specific ART regimens/combinations inuse) on HPV incidence, persistence, and type distribution will be evaluated.In conclusion, HPV persistence was examined in this longitudinal study of Kenyanwomen, approximately half of whom were HIV-infected, receiving effective ART, andhad re-constituted immune systems based on satisfactory CD4 cell counts. Persistentdetection of any HPV, HR-HPV, IARC HR-HPV, and LR-HPV types were all significantlyhigher in HIV-infected women compared to HIV-uninfected women. In addition to HIVinfection, factors associated with an increased risk of HPV persistence included ahigher number of lifetime sex partners. Factors associated with a decreased risk ofHPV persistence included older age and being married. To prevent cervical cancer, amalignancy caused by persistent HR-HPV infection, it is important to study andunderstand the behavioral and specific immunological defects that remain inHIV-infected women receiving ART that allow HPV to persist. Further studies are alsoneeded to determine the causes and significance of LR-HPV persistence inHIV-infected Kenyan women.Click here for additional data file.Supplemental material, Project_1_questionnaire for Persistence of oncogenic andnon-oncogenic human papillomavirus is associated with human immunodeficiencyvirus infection in Kenyan women by Yan Tong, Philip Tonui, Aaron Ermel, OmengeOrang’o, Nelson Wong, Maina Titus, Stephen Kiptoo, Kapten Muthoka, Patrick JLoehrer and Darron R Brown in SAGE Open Medicine


Option recommended by World Health Organization (WHO) includes human papillomavirus (HPV) primary screening followed by visual inspection with acetic acid (VIA) triage. We implemented a program based on a 3T‐approach (Test‐Triage and Treat). Our objective was to verify the effectiveness of the program by defining a set of performance indices. A sensitization campaign was performed in Dschang (Cameroon) and women aged 30‐49 years were invited to participate for screening based on the 3T‐approach. Participants performed HPV self‐sampling (Self‐HPV), analyzed with the point‐of‐care Xpert HPV assay followed by VIA/VILI triage and treatment if required. Key performance indicators (KPIs) for screening, diagnosis, treatment and follow‐up were defined, and achievable targets were described for which the approach is likely to be running optimally. A total of 840 women with a mean age of 39.4±5.9 years participated. The KPIs included (i) the screening rate , (ii) HPV positivity rate , (iii) compliance to referral to VIA/VILI and complete test , (iv) compliance to referral to thermal ablation , (v) VIA/VILI positivity rate , (vi) a single visit from diagnostic to treatment , (vii) compliance to follow‐up at 1 month  and (viii) at 6 months . Program performance based on the single‐visit 3T‐approach corresponded to defined targets and preliminary results support adequateness of KPIs for periodic monitoring. The study shows the performance of screening for cervical cancer in a single visit, using the 3T strategy, for Test‐Triage and Treat in low‐income countries Our results will be of great interest especially those designing and conducting women’s health screening programs in low‐income countries. Improved primary screening, diagnosis, treatment, and follow‐up, such as in the single‐visit 3T approach to screen cervical cancer in Cameroon, will substantially reduce the incidence of preventable or treatable diseases in low‐ and middle‐income countries. To monitor the quality of the program and to ensure that desired outcome are achieved, it is necessary to use a data collection tool to identify problem and plan corrective actions..The aim of this study was to assess quantitatively how a screening program based on the 3T‐approach can be evaluated and monitored. For this purpose, over a 7‐month pilot phase, we defined a set of key performance indicators (KPIs) including corresponding targets or standards against which performance was assessed.22.1The 3T‐approach was introduced in September 2018, in the District Hospital of Dschang, a rural city located in the West Province of Cameroon, with an estimated population of 220’000 inhabitants. The program, which is scheduled for 5 years, is based on the WHO recommendations to screen women aged 30‐49 years at least once in a 5‐year period. According to the national census, we estimated that about 10’000 women should be screened in order to obtain an 80% coverage of this targeted population.Regarding the recruitment, at the beginning of the campaign, women living in town were brought in by word of mouth. Then we used different methods such as talks in community centers, churches and women association's group. We have made radio advertisements and banners. And then we mobilized and trained community health workers to reach out to women living in different rural area to improve women's participation.The local team organized a one‐hour session daily for the women willing to be screened, in order to sensitize participants about CC, HPV and CC prevention. After this information session, all women aged 30‐49 years were included in the study after full understanding of the procedure, and an informed consent form, available in French and in English, was signed. Exclusion criteria were pregnancy and previous total hysterectomy. This study was approved by the Ethical Cantonal Board of Geneva, Switzerland and the Cameroonian National Ethics Committee for Human Health Research. It was registered at ClinicalTrials.gov number NCT03757299.The study procedure was divided in four steps: (a) a case report form (CRF) on socio‐demographic data and medical history was completed by a midwife; (b) woman performed a Self‐HPV with a flocked swab , and the result was given within 1 hour. During this time, the women completed a questionnaire on the acceptability of Self‐HPV; (c) if HPV was negative, women were reassured and advised to repeat the test in 5 years; if HPV was positive, a pelvic examination was completed by the midwife. VIA, D‐VILI; (d) if the provider visualized an acetowhite or iodo‐negative lesion, the procedure was completed by thermal ablation  or the patient was referred for LEEP if non eligible. In case of invasive cancer, the woman was led to the gynecologic department to get a full assessment and treatment that was completely covered by the program. All data regarding the gynecological examination and treatment were recorded in the patient's file.For quality control, cytology and biopsies were performed for all HPV positive women, but results are not reported here. Local staff was trained through an e‐learning platform managed by physicians from the University of Geneva and Dschang. One week of theoretical course followed by one week of practical training were required. After two weeks of training, review of normal and abnormal cervical photographs as well as clinical sessions to observe and practice the technique were organized. At the end of the training, a theoretical and practical exam was performed to ensure that all the necessary skills were acquired. Health care providers were certified by the University of Geneva and Dschang. After the implementation of the 3T‐approach physicians and consultants continued to provide training to nurses, to verify quality improvement efforts and help manage difficult cases. The files of digital smartphone photographs are used for review and quality improvement.2.2® uses PCR to detect the DNA of 14 high risks HPV. Specifically, it identifies types HPV 16 and HPV 18/45 in two distinct detection channels (channel 1 and 2), and reports 11 other high‐risk types  in a pooled result, after detection in three distinct channels.Participants performed self‐HPV by themselves and those having difficulties were assisted by the health staff. The swab was then plunged into a vial containing 20 ml NaCl 0.9% solution, and then vortexed for 30‐45 seconds. One milliliter of the solution was collected with a Pipetman and then transferred into a single‐use disposable cartridge that holds PCR reagents of the GeneXpert® machine . The Xpert HPV assay2.3During pelvic examination, VIA and VILI inspection were done to detect precancerous lesions. Only lesions localized into the transformation zone were considered as significant.2.4We used a Samsung Galaxy® S5 (16 Megapixels) and the application named “Exam”.2.5We used a thermocoagulator , which heats a probe at 100° Celsius. This probe was applied on the precancerous lesion for 60 seconds to eliminate the abnormal zone.2.6Women who received a treatment  are reconvened one month and six months after the procedure. The control at one month consists of a clinical exam. Then at six month they will have an HPV test, a VIA/VILI inspection and cytology and biopsies. If the cytology or biopsy is positive, they will be reconvened for treatment.2.7The sociodemographic and medical data and health outcomes were first collected by midwives on CRF‐paper during anamnesis and screening. All data including treatment and follow‐up were later registered on SecuTrial® software database by trained doctor. Data are monitored monthly. Screening results and treatment decision of midwives is recorded daily and transcribed on our database, as well as the monthly assessment of their clinical practice.2.8Performance threshold have been defined for each KPI with the aim of attain an achievable target or expected range that was developed according to previous studies and local conditions2.9Quantitative data were entered and analyzed using Stata Statistical Software Release 13 . A descriptive analysis was conducted; categorical variables were summarized with frequencies and percentage, and continuous variables were summarized with means and standard deviations (SD). Women's socio‐demographic and medical data were collected, stored, and managed by the SecuTrial online database.33.1A total of 840 women participated in the CC screening campaign during the study period Table . Average3.2Overall, 166 patients were HPV positive, corresponding to a positivity of 19.8%. The results showed that 3.6% (n = 6) of women were infected by HPV 16, 13.9% n = 23) by 18/45 and 77.1% (n = 128) by “other” HR HPV. Combined infections were found in 4.1% (n = 9) of women , no woman stopped her treatment because of pain or discomfort and all of them have received the therapy  the rate of women screened was 8.4% (840/10 000) (target 20% for 12 months), (b) the HPV positivity was 19.8% (expected range 18%‐25%), (c) the number of HPV‐positive women who accepted to participate and received VIA/VILI and D‐VIA/VILI testing was 100% (target > 90%) and (d) the number of VIA/VILI‐positive women who accepted treatment and received the complete therapy (target > 90%. Other KPI registered in the 3T process were (e) the VIA/VILI positivity rate, which reached 50.6% (range 45%‐55%), (f) the rate of patient having a 3T process conducted in a single visit, which was 79.8% (target > 80%), (g) follow‐up at one month which was 96.4% (target > 80%) and (h) at 6 months which was 70.6% (target > 80%) . Associating testing with an immediate offer of triaging and treatment for screen‐positive cases is probably the best way to reduce the loss of follow‐up.We found a VIA/VILI positivity rate of 50.6% among HPV‐positive women, which is higher to what was described in previous studies conducted in population with unknown HPV status,Our study has some limitations that need to be addressed. First, it was conducted in a single site with a relatively small sample size. Second, data need to be evaluated in a centralized office that serves different health facilities. Finally, it is a preliminary analysis, so results may not be generalized beyond the purpose of the study.Strength of this study is the high quality of data collection as part of routine care, which allow to evaluate quality of the programs and formulate specific recommendations regarding the 3T‐approach.Using KPIs measures is considered as having an important impact on patient safety, monitoring and quality improvement of a CC screening program.In conclusion, the performance of the 3T‐approach in rural Cameroon can be assessed with a minimum set of key indicators. The analysis demonstrated that the program works adequately whereas it is necessary to define a periodic assessment of KPIs to assure a continuous improvement. This study could help low income countries planning to scale up outcome indicators of interest for their program based on primary HPV testing and treatment in a single visit.None.MdP and JL led content development and writing of the article. PP and PV provided conceptual input, reviewed and edited article drafts. BK, EFT, and JTF wrote content on Cameroon, described the 3T procedure in Dschang and edited article drafts. RC provided statistical analysis and edited article drafts. JS and CF organized the health information system, provided data, and edited article drafts. The database is available as needed.