Household Socioeconomic and Demographic Correlates of <i>Cryptosporidium</i> Seropositivity in the United States

<div><p>Background</p><p><i>Cryptosporidium</i> are parasitic protozoa that infect humans, domestic animals, and wildlife globally. In the United States, cryptosporidiosis occurs in an estimated 750,000 persons annually, and is primarily caused by either of the <i>Cryptosporidium parvum</i> genotypes 1 and 2, exposure to which occurs through ingestion of food or water contaminated with oocytes shed from infected hosts. Although most cryptosporidiosis cases are caused by genotype 1 and are of human origin, the zoonotic sources of genotype 2, such as livestock, are increasingly recognized as important for understanding human disease patterns. Social inequality could mediate patterns of human exposure and infection by placing individuals in environments where food or water contamination and livestock contact is high or through reducing the availability of educational and sanitary resources required to avoid exposure.</p><p>Methodology/Principal Findings</p><p>We here analyzed data from the National Health and Nutritional Examination Survey (NHANES) between 1999 and 2000, and related seropositivity to <i>Cryptosporidium parvum</i> to correlates of social inequality at the household and individual scale. After accounting for the complex sampling design of NHANES and confounding by individual demographics and household conditions, we found impaired household food adequacy was associated with greater odds of <i>Cryptosporidium</i> seropositivity. Additionally, we identified individuals of non-white race and ethnicity and those born outside the United States as having significantly greater risk than white, domestic-born counterparts. Furthermore, we provide suggestive evidence for direct effects of family wealth on <i>Cryptosporidium</i> seropositivity, in that persons from low-income households and from families close to the poverty threshold had elevated odds of seropositivity relative to those in high-income families and in households far above the poverty line.</p><p>Conclusions/Significance</p><p>These results refute assertions that cryptosporidiosis in the United States is independent of social marginalization and poverty, and carry implications for targeted public health interventions for <i>Cryptosporidium</i> infection in resource-poor groups. Future longitudinal and multilevel studies are necessary to elucidate the complex interactions between ecological factors, social inequality, and <i>Cryptosporidium</i> dynamics.</p></div

<i>Cryptosporidium parvum</i> IgG seropositivity to the 17kDA and 27kDA antigens among persons aged 6–49 in the United States, NHANES 1999–2000.

<p>^a Percentages in each row give the proportion of each variable group with a negative or positive IgG response to the 17kDA and 27kDA antigens relative to the column total. Statistics in bold show covariates where <i>p</i> < 0.15 from a Satterthwaite-adjusted <i>F</i> statistic via a Wald test with survey-adjusted degrees of freedom.</p><p><i>Cryptosporidium parvum</i> IgG seropositivity to the 17kDA and 27kDA antigens among persons aged 6–49 in the United States, NHANES 1999–2000.</p

Cost-Effectiveness Analysis of Community Active Case Finding and Household Contact Investigation for Tuberculosis Case Detection in Urban Africa

<div><p>Introduction</p><p>Case detection by passive case finding (PCF) strategy alone is inadequate for detecting all tuberculosis (TB) cases in high burden settings especially Sub-Saharan Africa. Alternative case detection strategies such as community Active Case Finding (ACF) and Household Contact Investigations (HCI) are effective but empirical evidence of their cost-effectiveness is sparse. The objective of this study was to determine whether adding ACF or HCI compared with standard PCF alone represent cost-effective alternative TB case detection strategies in urban Africa.</p><p>Methods</p><p>A static decision modeling framework was used to examine the costs and effectiveness of three TB case detection strategies: PCF alone, PCF+ACF, and PCF+HCI. Probability and cost estimates were obtained from National TB program data, primary studies conducted in Uganda, published literature and expert opinions. The analysis was performed from the societal and provider perspectives over a 1.5 year time-frame. The main effectiveness measure was the number of true TB cases detected and the outcome was incremental cost-effectiveness ratios (ICERs) expressed as cost in 2013 US$per additional true TB case detected.</p><p>Results</p><p>Compared to PCF alone, the PCF+HCI strategy was cost-effective at US$443.62 per additional TB case detected. However, PCF+ACF was not cost-effective at US$1492.95 per additional TB case detected. Sensitivity analyses showed that PCF+ACF would be cost-effective if the prevalence of chronic cough in the population screened by ACF increased 10-fold from 4% to 40% and if the program costs for ACF were reduced by 50%.</p><p>Conclusions</p><p>Under our baseline assumptions, the addition of HCI to an existing PCF program presented a more cost-effective strategy than the addition of ACF in the context of an African city. Therefore, implementation of household contact investigations as a part of the recommended TB control strategy should be prioritized.</p></div

Decision Tree for the Passive Case Finding Strategy.

<p>Decision Tree for the Passive Case Finding Strategy.</p

One-way Sensitivity Analysis for Cost-effectiveness of TB Case Finding Strategies Varying Probabilities and Costs.

<p>^aICER = Incremental Cost- Effectiveness Ratio</p><p>^b Ranges obtained from published literature, expert opinion, or full ranges used</p><p>^<b>c</b> PCF+ACF becomes cost-effective at high probability of chronic cough, ICER below decision threshold of US$ 1,102.00</p><p>^d PCF+HCI is no longer cost effective at low probability of case detection, ICER above decision threshold</p><p>^<b>e</b> PCF+ACF becomes a cost-effective at low ACF program cost, ICER below decision threshold</p><p>One-way Sensitivity Analysis for Cost-effectiveness of TB Case Finding Strategies Varying Probabilities and Costs.</p

Incremental Cost-effectiveness Ratios from the Societal Perspective Referencing PCF as a Common Baseline.

<p>a: Effectiveness are rounded to the nearest whole number per 1000 person screened in the target population</p><p>b: ICER- Incremental Cost-Effectiveness Ratio (incremental cost divided by incremental effectiveness)</p><p>*calculations of ICERs do not exactly match direct division of incremental cost and incremental effectiveness as shown in table because we used up to 5 significant digits for effectiveness numbers to increase precision and minimize rounding errors</p><p>Incremental Cost-effectiveness Ratios from the Societal Perspective Referencing PCF as a Common Baseline.</p

Summary of Cost (in 2013US$) Estimates Associated with TB Detection.

<p>a: Program costs include administration, transport, communication & health personnel</p><p>b: Direct medical costs include Smear tests, culture tests, CXR & consumable supplies</p><p>c: Total patient and care giver costs include direct (transportation& meals) and, Indirect costs (productivity/wages lost)</p><p>d: Estimated total per patient costs are a summation of program, direct medical and total patient-caregiver costs estimated in each strategy</p><p>Summary of Cost (in 2013US$) Estimates Associated with TB Detection.</p

Decision Tree for the Passive Case Finding <i>plus</i> Active Case Finding Strategy.

<p>Decision Tree for the Passive Case Finding <i>plus</i> Active Case Finding Strategy.</p

Incremental Cost-effectiveness Ratios from the Provider Perspective Referencing PCF as a Common Baseline.

<p>a: Effectiveness are rounded to the nearest whole number per 1000 person screened in the target population</p><p>b:ICER- Incremental Cost-effectiveness Ratio (incremental cost divided by incremental effectiveness)</p><p>*calculation of ICERs do not exactly match direct division of incremental cost and incremental effectiveness as shown in table because we used up to 5 significant digits for effectiveness numbers to increase precision and minimize rounding errors</p><p>Incremental Cost-effectiveness Ratios from the Provider Perspective Referencing PCF as a Common Baseline.</p

Probabilities Estimates Used in Decision Analytic Model.

<p>Probabilities Estimates Used in Decision Analytic Model.</p