Current Infection Rates Research Articles

A Survey of the Prevalence of Infections Present among Inpatients in a Tertiary Care Hospital in 2023

Objective: To explore the current infection rate among inpatients in a tertiary hospital in 2023, to understand the infection situation in the hospital, and to provide a reliable basis for carrying out further hospital infection prevention and control and other work. Methods: Inpatients of a tertiary hospital on a certain date in 2023 were selected, and the survey data were extracted with the Apricot Grove real-time monitoring system using a combination of questionnaires and medical record data. Results: The infection rate was 12.63%, of which the hospital infection rate was 2.25% and the community infection rate was 10.38%. Lower respiratory tract infections accounted for 77.28% of the community infections, and lower respiratory tract infections accounted for 73.44% of the cases of hospital infections, with a total of 44 strains of pathogens isolated from hospital infections, and a total of 218 strains of pathogens isolated from community infections. The total application rate of antimicrobial drugs was 31.67%, the proportion of prophylactic drugs in the whole hospital was 9.66%, the proportion of therapeutic drugs was 90.33%, and the rate of bacterial culture delivery was 39.18%. Conclusion: The infection rate survey truly reflects the dynamics of infection in this hospital, makes clearer the key departments and key links of hospital infection prevention and control, further provides the basis for targeted infection control, and improves the knowledge and execution of hospital infection prevention and control by medical staff.

Investigating long-term outcomes and predictors of primary outcomes in patients treated for cardiac implantable electronic device infections

Abstract Background The estimated current infection rate after cardiac implantable electronic devices (CIED) implantation ranges between 1% and 2%, with variations in the literature from 0.13% to 12.6% (2). The rise in CIED implantation rates over the years has led to an escalation in the frequency of device-related infections. This trend is compounded by the elongation of patient comorbidities and life expectancy (3). Purpose The study aimed to investigate the primary outcome rates (including death, myocardial infarction (MI), cerebrovascular accidents (CVA), and reinfection) and identify predictors of primary outcomes in patients receiving treatment for CIED infection. Methods A retrospective analysis was conducted at a single-center. The study encompassed 2322 patients who sought treatment at the arrhythmia clinic of our Institute between March 2011 and July 2020 and underwent CIED implantation. After excluding 20 patients with active infections and 3 patients postoperative cardiac arrest, 36 patients were diagnosed with CIED infection (1.55% incidence). Diagnosis was based on the Novel 2019 International CIED Infection Criteria. Patients were categorized into groups based on the occurrence of all-cause death, MI, CVA, and reinfection during the follow-up period. Results The median follow-up period post admission with CIED infection was 42.5 (7-141) months. Table 1 presents patient characteristics, procedure details, and management-related parameters in the groups stratified by the primary endpoint. Notably, 58.3% of the patients had previously undergone a replacement procedure. Among patients with CIED infection, reinfection was observed in 20.0% of those who had a de novo procedure and 38.1% of those who underwent a secondary procedure (p: 0.25). Cox regression analysis revealed that pre-procedure C-reactive protein (CRP) levels and CHA2DS2-VASc score were independent predictors of the primary outcome (OR: 1.03 (1.00-1.06); P: 0.035, OR: 1.34(1.03-1.88); P: 0.030, respectively) (Table 2). Conclusion Long-term outcomes in patients with CIED infection appear to be correlated with pre-procedure CRP levels, indicating the severity of infection, and the CHA2DS2-VASc score, providing valuable insights into patient comorbidities. These factors seem to outweigh the impact of the specific procedure and antibiotic regimens administered. Management should not only focus on the history of CIED infection during follow-up but also prioritize the management of existing comorbidities to improve outcomes. Given the study's limitations such as the small sample size and retrospective nature, further investigations are warranted to confirm these findings.Table 1Table 2

Estimating the risk of SARS-CoV-2 infection in New Zealand border arrivals

BackgroundTravel restrictions and border controls were used extensively during the COVID-19 pandemic. However, the processes for making robust evidence-based risk assessments of source countries to inform border control policies was in many cases very limited.MethodsBetween April 2020 and February 2022, all international arrivals to New Zealand were required to spend 14 days in government-managed quarantine facilities and were tested at least twice. The infection rates among arrivals in the years 2020, 2021 and 2022 were respectively 6.3, 9.4 and 90.0 cases per thousand arrivals (487, 1064 and 1496 cases). Test results for all arrivals were linked with travel history, providing a large and comprehensive dataset on the number of SARS-CoV-2-positive and negative travellers from different countries over time. We developed a statistical model to predict the country-level infection risk based on infection rates among recent arrivals and reported cases in the country of origin. The model incorporates a country-level random effect to allow for the differences between the infection risk of the population of each country and that of travellers to New Zealand. A time dependent auto-regressive component of the model allows for short term correlation in infection rates.ResultsA model selection and checking exercise found that the model was robust and reliable for forecasting arrival risk for 2 weeks ahead. We used the model to forecast the number of infected arrivals in future weeks and categorised countries according to their risk level. The model was implemented in R and was used by the New Zealand Ministry of Health to help inform border control policy during 2021.ConclusionsA robust and practical forecasting tool was developed for forecasting infection risk among arriving passengers during a period of controlled borders during the COVID-19 pandemic. The model uses historical infection rates among arrivals and current infection rates in the source country to make separate risk predictions for arrivals from each country.

Literacy and attitude of Asian youths on dengue and its prevention in an endemic developed community.

Over the past few decades, the incidence of dengue fever has considerably increased. Effective vector control strategies and specific protection using dengue vaccine are thought to be the key elements to combat dengue. The dengue incidence among the Singapore youths (15-24 years) was second only to that of adults (25-44 years). This study evaluated the knowledge and attitude of Singapore youths on dengue and its preventive measures. A cross-sectional study using online-based questionnaire survey was conducted among Singapore youths from September to November 2022. Data were analyzed for descriptive statistics whereas Chi-squared test, linear regression analysis and Pearson correlation were used to determine the association between demographic factors and youth's attitude on dengue prevention using Rstudio. A total of 624 respondents completed the survey out of 1822 surveys distributed nation-wide, with a response rate of 34.2% (mean age 17.4 years 1.84; 59.3% female; 89.9% Chinese). The mean dengue knowledge scores of participants were 14.1 2.8. Univariate analysis showed that teenagers (15-19 years) had significantly higher knowledge score than the young adults (20-24 years) (=0.82,95%CI = 0.13-1.51, p = 0.021). Majority of them were aware of the Mozzie Wipeout campaign (90.2%) followed by the release of Wolbachia mosquitos (69.1%). Two-thirds of the youths who were aware of Wolbachia and Gravitrap considered that it was effective in reducing dengue infection rates. Participants suggested information about the current dengue infection rate (71.9%) as the most effective of the five proposed strategies to improve uptake of dengue preventive measures. In comparison to young adults, teenagers were more likely to uptake dengue preventive measures if widespread mosquito control practices were implemented (69.1% vs. 42.3%). The overall knowledge of the youths on dengue and its prevention was satisfactory. Future health promotion campaigns targeting the youths should focus on transforming the knowledge into practice.

Prevalence and influential factors of isolated hepatitis B core antibody positivity in a Chinese adult population

Isolated anti-HBc (IAHBc) is defined by the presence of anti-HBc in the absence of HBsAg and hepatitis B surface antibody (anti-HBs). IAHBc is of great clinical significance as a specific pattern of HBV infection, but IAHBc has not been fully clarified. This study aimed to explore the prevalence and influential factors of IAHBc from routine examination results of inpatients.A total of 61,247 individuals were included in the study, with a median age of 55 years (range: 43–68), and a male-to-female ratio of 0.90:1. The prevalence of current HBV infection (HBsAg positive) was 6.82%, while the prevalence of previous HBV infection (HBsAg negative but anti-HBc positive) was 48.63%. The prevalence of IAHBc was 12.31%. Among them, the rates for males were 7.10%, 52.16%, and 13.70%, respectively, which were significantly higher than the rates for females at 6.56%, 45.45%, and 11.06% (P < 0.05). The prevalence rates mentioned above were significantly reduced after vaccination (P < 0.05). The prevalence of IAHBc increases with age, rising from 0.23% in the age group of 15–29 years to 13.57% in individuals aged 80 and above. After the age of 50, the prevalence of IAHBc closely parallels the previous infection rate but shows no significant association with the current infection rate (P > 0.05). Among IAHBc individuals, approximately 33.83% tested positive for anti-HBe, and their anti-HBc absorbance values were significantly higher compared to anti-HBe negative individuals (7.08 and 5.31, P < 0.01). The prevalence of anti-HBe positivity among IAHBc individuals does not vary with changes in the previous infection rate and age (P > 0.05).

Real-Time data integration in diagnostic devices for predictive modeling of infectious disease outbreaks

The integration of real-time data in diagnostic devices is transforming the landscape of infectious disease management by enabling predictive modeling of outbreaks. Traditional diagnostic approaches, often constrained by delayed data processing and analysis, fall short in rapidly evolving scenarios like infectious disease outbreaks. Recent advancements in real-time data integration are addressing these limitations, offering significant improvements in predictive accuracy and timely response. Real-time data integration leverages continuous streams of information from various sources, including diagnostic devices, electronic health records, and environmental sensors, to provide a comprehensive view of disease dynamics. By incorporating this data into predictive models, healthcare professionals can better anticipate and manage outbreaks. For instance, integrating data from wearable sensors and mobile health applications allows for continuous monitoring of health indicators, which can signal early warning signs of disease spread. This approach enhances the ability to detect patterns and anomalies that might indicate an impending outbreak. Moreover, predictive modeling powered by real-time data facilitates proactive interventions. By analyzing trends and correlations in real-time, these models can forecast potential outbreak scenarios, optimize resource allocation, and guide public health responses. For example, predictive models can forecast the spread of diseases based on current infection rates and social behavior patterns, enabling targeted interventions and timely public health advisories. Despite the benefits, the integration of real-time data into diagnostic devices presents several challenges. Ensuring data accuracy and consistency, maintaining privacy and security, and managing the vast amounts of data generated are critical issues that need addressing. Advanced data analytics and machine learning techniques are essential for processing and interpreting this data effectively. Additionally, interoperability among various data sources and systems is crucial for a seamless integration process. In summary, the integration of real-time data in diagnostic devices offers a powerful tool for predictive modeling of infectious disease outbreaks. It enhances the accuracy of forecasts, improves response strategies, and ultimately contributes to more effective management of public health crises. As technology advances, addressing the associated challenges will be key to maximizing the potential of this innovative approach. Keywords: Real-Time, Data Integration, Diagnostic Devices, Predictive Modeling, Infectious Disease Outbreaks.

Application of a composite, multi-scale COVID-19 mitigation framework: US border use-case

ABSTRACT Airborne pathogen transmission within crowded facilities can be modelled by combining several interrelated mechanisms of spread: movement of people, airflow dynamics, and aerosol dispersion. This paper describes a composite model framework combining analytical models to demonstrate the spread of an airborne pathogen in a crowded, confined space at an immigrant processing centre on the southern US border during the border crisis of March 2021. Recommendations that could reduce current COVID-19 infection rate from 11% to 6.16% at relatively low additional cost to the government are given. These recommendations could also lower the infection rate by approximately five times from 31.14% worst case from long indoor exposures down to 6.35% when immigrant processing times surge to 10 days. This work highlights the challenges of managing COVID-19 in crowded facilities, and provides quantitative decision options with potential both to slow and prevent disease spread, while lessening the economic burden on communities.

Financial Analysis of Preoperative Nasal Decolonization With Povidone-Iodine in Closed Pilon Fracture Definitive Fixation

The purpose of this study is to determine the financial practicality for the use of nasal povidone-iodine (NP-I) in the preoperative holding area in attempt to decrease the rate of infection that is associated with operative fixation of closed pilon fractures. Institutional costs for treating postoperative infection following a closed pilon fracture, along with costs associated with preoperative NP-I use, were obtained. A break-even equation was used to analyze these costs to determine if the use of NP-I would decrease the current infection rate (17%) enough to be financially beneficial for routine use preoperatively. The total cost of treating a postoperative infection was found to be $18,912, with the cost of NP-I being $30 per patient dose. Considering a 17% infection rate and utilizing the break-even equation, NP-I was found to be economically viable if it decreased the current infection rate by 0.0016% (Number Needed to Treat=63,051.7). This break-even model suggests that the use of NP-I in the preoperative holding area is financially beneficial for decreasing the rate of infection associated with the treatment of closed pilon fractures.

Blocking Respiratory Syncytial Virus infection utilizing decoy ICAM-1 receptor proteins

Abstract Respiratory syncytial virus (RSV) infections result in a significant number of hospitalizations for young children and the elderly each year, and current infection rates continue to rise, leading to a substantial public health burden. While numerous vaccine candidates are in clinical trials, there is currently no approved RSV vaccine to prevent infection or antiviral treatment after infection. There is an urgent need to find new therapeutics and strategies that reduce severe RSV disease that could improve health and save lives. The RSV fusion (F) protein is critical for binding host cells and mediating infection and is the target of most candidate vaccines. The RSV F protein has been shown to interact with several host-cell surface receptor proteins such as Intercellular Adhesion Molecule 1 (ICAM-1), NCL, EGFR, IGF1R, and infect respiratory epithelial cells. In this study, we confirmed ICAM-1 could bind RSV F protein and inhibit RSV infection via an RSV neutralization assay. Using RSV F protein as bait, we immunoprecipitated RSV F interacting proteins from A549 respiratory cells and performed mass spectrometry analysis to identify novel host proteins that bind RSV F protein. Finally, we engineered a mRNA-lipid nanoparticle (LNP) expressing soluble ICAM-1. The goal is to utilize the ICAM-1 mRNA-LNP as a passive intranasal vaccine that would result in over-expressed soluble ICAM-1 in respiratory mucosal surfaces to function as a decoy receptor that would reduce RSV infection. We are evaluating this therapeutic approach in preclinical models as a prophylactic or treatment after infection. ICAM-1 mRNA-LNP may provide a novel defensive strategy to reduce RSV infection or disease severity and augment future RSV vaccines that become approved. Children’s Mercy Research Partners

A combined antibody and DNA assay for EBV infection in children.

ObjectiveThis paper studied the Epstein–Barr virus (EBV) infection status and influencing factors among children using a combined detection of specific antibodies and DNA.MethodsWe retrospectively analyzed children who visited the Affiliated Hospital of Hangzhou Normal University from January 2019 to December 2020, and correlations between the social environment and clinical data were analyzed.ResultsThe cumulative positive rates of specific antibody, DNA, and combined detection of EBV were 52.4%, 39.5%, and 54.0% (P = 0.001), respectively. The current infection rate was 15.7%, and the peak of infection occurred in the preschool group (P = 0.021). After adjusting for confounding factors, the number of siblings (OR = 1.550) and family members who smoke (OR = 1.524) were independent risk factors for EBV infection, whereas parents with a higher education level (OR = 0.493, OR = 0.316), longer breastfeeding time (OR = 0.578) and dedicated tableware (OR = 0.573) were independent protective factors.ConclusionA combination of antibody and DNA tests may be beneficial for the diagnosis of EBV infection. The EBV infection rate in children at our hospital was lower than the national average. Furthermore, the infection rate is closely related to the number of siblings, regardless of whether family members smoke, the status of parents' education, breastfeeding duration, and meal patterns. Overall, prevention measures should focus on the preschoolers.

Chlamydia infection, PID, and infertility: further evidence from a case–control study in China

BackgroundChlamydia trachomatis infection and pelvic inflammatory disease (PID) are well-known risk factors for female infertility. But there is limited evidence from China. This study aimed to further explore the associations between previous/current chlamydial infection, PID, and infertility in China.MethodsWe performed a 1:2 matched case–control study with two control groups: pregnant controls and non-pregnant controls in China in 2019. Women diagnosed with infertility were selected as cases (n = 255). Controls were selected based on the following criteria: Pregnant women who were documented in the selected hospitals were chosen as Pregnant controls (n = 510), and people who sought health care in Obstetric/Gynecologic clinics, Family Planning clinics, Dermatology and STD Department or Urological department were selected as Non-pregnant controls (n = 510). Infertility induced by male factors and people who used antibiotics in the vagina within two weeks were excluded. The first-stream specimen of urine samples was tested for chlamydia by nucleic acid amplification testing (NAAT). Conditional logistic regression was used to estimate the association.ResultsThe prevalence of previous chlamydial infection and PID were significantly higher in cases (2.4%, 17.3%) than in controls (Non-pregnancy: 0.4%, 3.0%; Pregnancy: 0.4%, 9.0%). The current chlamydial infection rates were 5.9%, 7.3%, and 7.1% in infertile, pregnant, and non-pregnant women, respectively. After adjusting for confounders, PID largely elevated the risk of infertility (using non-pregnant controls: adjusted OR = 2.57, 95% CI 1.51, 4.39; using pregnant controls: adjusted OR = 6.83, 95% CI 3.47, 13.43). And the positive association between PID and tubal infertility was more obvious for both groups. For current chlamydial infection, none of the odds ratios were significant at the 0.05 level, while small sample size limited the evaluation of an association between prior chlamydial infection with infertility.ConclusionsPrevious PID was indicated to largely increase the risk of infertility, especially tubal infertility. And there should be continuing emphasis on highly sensitive and specific biomarker for prior chlamydial infection.

Willingness to be vaccinated against COVID-19 is equal in individuals with affective disorders and healthy controls

BackgroundAffective disorders such as major depressive disorder and bipolar disorder are associated with higher infection rates and a more severe course of coronavirus disease (COVID-19). In turn, COVID-19 could trigger mental disease relapse. Vaccinations lead to a reduction of infections and the prevention of severe courses. This work aims to survey the willingness of individuals with affective disorders to get vaccinated and concerns about vaccinations. Methods: An online study (April–May 2021) assessed the current infection and vaccination rate amongst individuals with affective disorder in Austria by surveying attitudes towards the vaccination, the willingness to get vaccinated soon and possible reasons for decision. The analyses included 59 individuals with affective disorders and 59 healthy controls, matched for sex and age. Results: There was an overall high willingness to get vaccinated against COVID-19. Individuals with affective disorders were more skeptical about vaccinations in general but there was no significant difference between the groups in the willingness to get vaccinated against COVID-19. In both groups reasons for waiting were mainly fears of acute and/or long-term side effects and the fast development of the vaccines. Limitations: It was a cross sectional design. Due to the online design, no objective rating of current psychopathological symptoms was assessed. Willingness to get vaccinated in general and against COVID-19 in particular were self-created variables, whereas item statistics and factor analysis were conducted. Discussion: Because of the higher risk for individuals with affective disorders, preventive strategies like vaccinating should be promoted in this group. It is important to help individuals with AD to overcome barriers such as negative beliefs and concerns about acute and/or long-term side effects.

Reflection of the Importance of Public Health System to Promote Pro-vaccination Behavior Regarding COVID-19 in Brazil

In Brazil, and worldwide, we are reaching a critical moment in the COVID-19 pandemic. As the number of virus mutations grows, a paradoxical stabilization in the number of vaccinated individuals is concerned. In this letter, our goal is to raise awareness about the fundamental role we believe public health systems have in promoting communication policies that inform, reassure, and encourage vaccination without compromising individuals' freedom. We do so by providing key demographics on vaccination rates in Brazil, contrasting current infection rates. Furthermore, we also raise a series of research questions that we believe should be timely addressed by the scientific community to generate empirical evidence that will support effective policy and public administration

Differential impacts of contact tracing and lockdowns on outbreak size in COVID-19 model applied to China

The COVID-19 pandemic has led to widespread attention given to the notions of “flattening the curve” during lockdowns, and successful contact tracing programs suppressing outbreaks. However a more nuanced picture of these interventions’ effects on epidemic trajectories is necessary. By mathematical modeling each as reactive quarantine measures, dependent on current infection rates, with different mechanisms of action, we analytically derive distinct nonlinear effects of these interventions on final and peak outbreak size. We simultaneously fit the model to provincial reported case and aggregated quarantined contact data from China. Lockdowns compressed the outbreak in China inversely proportional to population quarantine rates, revealing their critical dependence on timing. Contact tracing had significantly less impact on final outbreak size, but did lead to peak size reduction. Our analysis suggests that altering the cumulative cases in a rapidly spreading outbreak requires sustained interventions that decrease the reproduction number close to one, otherwise some type of swift lockdown measure may be needed.

Opinion on the Policy of Lifting Restrictions to Entry Under the Circumstance of the COVID-19 Pandemic

Opinion on the Policy of Lifting Restrictions to Entry Under the Circumstance of the COVID-19 Pandemic

Spreading Analysis of COVID-19 Epidemic in Bangladesh by Dynamical Mathematical Modelling

The coronavirus disease 2019 (COVID-19), which emerged from Wuhan, China, is now a pandemic, affecting across the globe. Bangladesh also is experiencing the rapid growth of COVID-19 infection and death cases started from 8th March 2020. The purpose of providing a simple yet effective explanatory model for prediction of the future evolution of the contagion and verification of the effectiveness of the containment and lockdown measures in Bangladesh. In this study, using a modified SIR (Susceptible-Infected-Recovered) model a forecast is generated to predict the trends of COVID-19 cases in Bangladesh. The epidemic model was proposed to accommodate the effects of lockdown and individual based precautionary measures. Data has been taken and analyzed for before and after the movement control order (MCO) and during the MCO period. Modified SIR model in this work offers us an idea how the outbreak would progress based on the current data. It also has estimated that, the peak in terms of the number of infected cases will start from last of June 2020. For the total population (100%) the model gets the peaks at 214875 (infected cases) and 7743 (death cases). For the 90% population, the model shows the peaks at 244356 (infected cases) and 9100 (death cases). Analysis revealed that the lockdown and recommended individual hygiene can slow down the outbreak but unable to eradicate the disease from the society. With the current infection and death rate and existing level of personal precautionary the number of infected individuals will be increasing.

Differences and similarities between the impact of the first and the second COVID-19-lockdown on mental health and safety behaviour in Germany.

BackgroundGovernmental restrictions of daily life are key elements in reducing the transmission of COVID-19, but they have also put a strain on people’s mental health. Preventive policies differ all over the world as well as over different periods of time, and depend mostly on current infection rates. In Germany, there were two periods of restraint of varying severity, during which the government used different combinations of containment and mitigation measures to protect risk groups and to lower the number of hospitalizations.MethodsIn two online studies, we aimed to determine differences and similarities in COVID-19-related fear, generalized anxiety, depression and distress levels, as well as in the adherence to safety behaviour between the first lockdown in March and April and the second lockdown in November.ResultsThis study showed continued high psychological burden and even increased levels of depression symptoms, as well as less safety behaviour in the second phase of restrictions.ConclusionsThe results hint at a prolonged negative impact on people’s mental health and their safety behaviour despite lesser restrictions in the second lockdown, which may be interpreted as pandemic fatigue and hence strengthens the argument for a low-threshold access to psychological care.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.

Business School Grades, Assessment Scores, and Dropout Rates in the Covid-19 Pandemic

In response to the Covid-19 pandemic, universities shifted from predominantly in-person learning to fully online instruction in early 2020. Subsequent semesters faced continued uncertainty regarding course modalities, with institutions adopting an idiosyncratic mix of formats dependent on current community infection rates. In this paper, we compare student performance in three Covid-19 affected semesters to performance in the previous two unaffected semesters. Performance is measured as course grades, scores on standardized course specific assessment tests, and the incidence of dropping, withdrawing, or earning a grade of an F. On average, we find grades trended significantly higher throughout the semester, although student performance on standardized course assessment tests and the incidence of students failing or dropping remained relatively unchanged. This was not true for all types of students. First-year and first-generation students did significantly worse throughout the pandemic in online courses, as compared to courses with some in-person element. In addition, women in courses with some in-person requirement reversed the usual penalty observed in business courses, outperforming otherwise equivalent male students in this modality.

Poverty in the time of epidemic: A modelling perspective.

We create a network model to study the spread of an epidemic through physically proximate and accidental daily human contacts in a city, and simulate outcomes for two kinds of agents—poor and non-poor. Under non-intervention, peak caseload is maximised, but no differences are observed in infection rates across poor and non-poor. Introducing interventions to control spread, peak caseloads are reduced, but both cumulative infection rates and current infection rates are systematically higher for the poor than for non-poor, across all scenarios. Larger populations, higher fractions of poor, and longer durations of intervention are found to progressively worsen outcomes for the poor; and these are of particular concern for economically vulnerable populations in cities of the developing world. Addressing these challenges requires a deeper, more rigorous understanding of the relationships between structural poverty and epidemy, as well as effective utilization of extant community level infrastructure for primary care in developing cities. Finally, improving iniquitous outcomes for the poor creates better outcomes for the whole population, including the non-poor.